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# Contributing to axolotl
First of all, thank you for your interest in contributing to axolotl! We appreciate the time and effort you're willing to invest in making our project better. This document provides guidelines and information to make the contribution process as smooth as possible.
## Table of Contents
- [Code of Conduct](#code-of-conduct)
- [Getting Started](#getting-started)
- [How to Contribute](#how-to-contribute)
- [Reporting Bugs](#reporting-bugs)
- [Suggesting Enhancements](#suggesting-enhancements)
- [Submitting Pull Requests](#submitting-pull-requests)
- [Style Guidelines](#style-guidelines)
- [Code Style](#code-style)
- [Commit Messages](#commit-messages)
- [Additional Resources](#additional-resources)
## Code of Conductcode
All contributors are expected to adhere to our [Code of Conduct](CODE_OF_CONDUCT.md). Please read it before participating in the axolotl community.
## Getting Started
Bugs? Please check for open issue else create a new [Issue](https://github.com/OpenAccess-AI-Collective/axolotl/issues/new).
PRs are **greatly welcome**!
1. Fork the repository and clone it to your local machine.
2. Set up the development environment by following the instructions in the [README.md](https://github.com/OpenAccess-AI-Collective/axolotl/tree/main/README.md) file.
3. Explore the codebase, run tests, and verify that everything works as expected.
Please run below to setup env
```bash
pip3 install -r requirements-dev.txt -r requirements-tests.txt
pre-commit install
# test
pytest tests/
```
## How to Contribute
### Reporting Bugs
If you encounter a bug or issue while using axolotl, please open a new issue on the [GitHub Issues](https://github.com/OpenAccess-AI-Collective/axolotl/issues) page. Provide a clear and concise description of the problem, steps to reproduce it, and any relevant error messages or logs.
### Suggesting Enhancements
We welcome ideas for improvements and new features. To suggest an enhancement, open a new issue on the [GitHub Issues](https://github.com/OpenAccess-AI-Collective/axolotl/issues) page. Describe the enhancement in detail, explain the use case, and outline the benefits it would bring to the project.
### Submitting Pull Requests
1. Create a new branch for your feature or bugfix. Use a descriptive name like `feature/your-feature-name` or `fix/your-bugfix-name`.
2. Make your changes, following the [Style Guidelines](#style-guidelines) below.
3. Test your changes and ensure that they don't introduce new issues or break existing functionality.
4. Commit your changes, following the [commit message guidelines](#commit-messages).
5. Push your branch to your fork on GitHub.
6. Open a new pull request against the `main` branch of the axolotl repository. Include a clear and concise description of your changes, referencing any related issues.
## Style Guidelines
### Code Style
axolotl uses [{codestyle}]({URLofCodestyle}) as its code style guide. Please ensure that your code follows these guidelines.
### Commit Messages
Write clear and concise commit messages that briefly describe the changes made in each commit. Use the imperative mood and start with a capitalized verb, e.g., "Add new feature" or "Fix bug in function".
## Additional Resources
- [GitHub Help](https://help.github.com/)
- [GitHub Pull Request Documentation](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests)
- [{codestyle}]({URLofCodestyle})
Thank you once again for your interest in contributing to axolotl. We look forward to collaborating with you and creating an even better project together!

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name: ci-cd
on:
push:
branches:
- "main"
workflow_dispatch:
jobs:
build-axolotl:
if: ${{ ! contains(github.event.commits[0].message, '[skip docker]]') && github.repository_owner == 'OpenAccess-AI-Collective' }}
strategy:
fail-fast: false
matrix:
include:
- cuda: 118
cuda_version: 11.8.0
python_version: "3.10"
pytorch: 2.1.2
axolotl_extras:
axolotl_args: "--extra-index-url https://download.pytorch.org/whl/cu118"
is_latest: true
- cuda: 121
cuda_version: 12.1.0
python_version: "3.10"
pytorch: 2.1.2
axolotl_extras:
- cuda: 121
cuda_version: 12.1.0
python_version: "3.11"
pytorch: 2.1.2
axolotl_extras:
runs-on: axolotl-gpu-runner
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Docker metadata
id: metadata
uses: docker/metadata-action@v5
with:
images: winglian/axolotl
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
# guidance for testing before pushing: https://docs.docker.com/build/ci/github-actions/test-before-push/
- name: Build and export to Docker
uses: docker/build-push-action@v5
with:
context: .
build-args: |
BASE_TAG=${{ github.ref_name }}-base-py${{ matrix.python_version }}-cu${{ matrix.cuda }}-${{ matrix.pytorch }}
CUDA=${{ matrix.cuda }}
PYTORCH_VERSION=${{ matrix.pytorch }}
AXOLOTL_ARGS=${{ matrix.axolotl_args }}
file: ./docker/Dockerfile
push: ${{ github.event_name != 'pull_request' }}
tags: |
${{ steps.metadata.outputs.tags }}-py${{ matrix.python_version }}-cu${{ matrix.cuda }}-${{ matrix.pytorch }}${{ matrix.axolotl_extras != '' && '-' || '' }}${{ matrix.axolotl_extras }}
${{ (matrix.is_latest) && format('{0}-latest', steps.metadata.outputs.tags) || '' }}
labels: ${{ steps.metadata.outputs.labels }}
build-axolotl-runpod:
needs: build-axolotl
if: ${{ ! contains(github.event.commits[0].message, '[skip docker]]') && github.repository_owner == 'OpenAccess-AI-Collective' }}
# this job needs to be run on self-hosted GPU runners...
strategy:
matrix:
include:
- cuda: 118
cuda_version: 11.8.0
python_version: "3.10"
pytorch: 2.1.2
axolotl_extras:
is_latest: true
- cuda: 121
cuda_version: 12.1.0
python_version: "3.10"
pytorch: 2.1.2
axolotl_extras:
- cuda: 121
cuda_version: 12.1.0
python_version: "3.11"
pytorch: 2.1.2
axolotl_extras:
runs-on: axolotl-gpu-runner
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Docker metadata
id: metadata
uses: docker/metadata-action@v5
with:
images: winglian/axolotl-cloud
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- name: Build
uses: docker/build-push-action@v5
with:
context: .
build-args: |
BASE_TAG=${{ github.ref_name }}-py${{ matrix.python_version }}-cu${{ matrix.cuda }}-${{ matrix.pytorch }}${{ matrix.axolotl_extras != '' && '-' || '' }}${{ matrix.axolotl_extras }}
CUDA=${{ matrix.cuda }}
file: ./docker/Dockerfile-cloud
push: ${{ github.event_name != 'pull_request' }}
tags: |
${{ steps.metadata.outputs.tags }}-py${{ matrix.python_version }}-cu${{ matrix.cuda }}-${{ matrix.pytorch }}${{ matrix.axolotl_extras != '' && '-' || '' }}${{ matrix.axolotl_extras }}
winglian/axolotl-runpod:main-py${{ matrix.python_version }}-cu${{ matrix.cuda }}-${{ matrix.pytorch }}${{ matrix.axolotl_extras != '' && '-' || '' }}${{ matrix.axolotl_extras }}
${{ (matrix.is_latest) && format('{0}-latest', steps.metadata.outputs.tags) || '' }}
${{ (matrix.is_latest) && format('{0}-latest', 'winglian/axolotl-runpod:main') || '' }}
labels: ${{ steps.metadata.outputs.labels }}

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f94acc56

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{
// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "Debug axolotl prompt - sharegpt",
"type": "python",
"module": "accelerate.commands.launch",
"request": "launch",
"args": [
"-m", "axolotl.cli.train", "dev_sharegpt.yml",
// The flags below simplify debugging by overriding the axolotl config
// with the debugging tips above. Modify as needed.
"--dataset_processes=1", // limits data preprocessing to one process
"--max_steps=1", // limits training to just one step
"--batch_size=1", // minimizes batch size
"--micro_batch_size=1", // minimizes batch size
"--val_set_size=0", // disables validation
"--sample_packing=False", // disables sample packing which is necessary for small datasets
"--eval_sample_packing=False",// disables sample packing on eval set
"--dataset_prepared_path=temp_debug/axolotl_outputs/data", // send data outputs to a temp folder
"--output_dir=temp_debug/axolotl_outputs/model" // send model outputs to a temp folder
],
"console": "integratedTerminal", // show output in the integrated terminal
"cwd": "${workspaceFolder}/devtools", // set working directory to devtools from the root of the project
"justMyCode": true, // step through only axolotl code
"env": {"CUDA_VISIBLE_DEVICES": "0", // Since we aren't doing distributed training, we need to limit to one GPU
"HF_HOME": "${workspaceFolder}/devtools/temp_debug/.hf-cache"}, // send HF cache to a temp folder
"preLaunchTask": "cleanup-for-dataprep", // delete temp folders (see below)
}
]
}

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.vscode/tasks.json vendored Normal file
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//this file is used by launch.json
{
"version": "2.0.0",
"tasks": [
// this task changes into the devtools directory and deletes the temp_debug/axolotl_outputs folder
{
"label": "delete-outputs",
"type": "shell",
"command": "rm -rf temp_debug/axolotl_outputs",
"options":{ "cwd": "${workspaceFolder}/devtools"},
"problemMatcher": []
},
// this task changes into the devtools directory and deletes the `temp_debug/.hf-cache/datasets` folder
{
"label": "delete-temp-hf-dataset-cache",
"type": "shell",
"command": "rm -rf temp_debug/.hf-cache/datasets",
"options":{ "cwd": "${workspaceFolder}/devtools"},
"problemMatcher": []
},
// this task combines the two tasks above
{
"label": "cleanup-for-dataprep",
"dependsOn": ["delete-outputs", "delete-temp-hf-dataset-cache"],
}
]
}

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<!DOCTYPE html>
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<meta charset="utf-8">
<meta name="generator" content="quarto-1.4.533">
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
<title>Axolotl</title>
<style>
code{white-space: pre-wrap;}
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div.columns{display: flex; gap: min(4vw, 1.5em);}
div.column{flex: auto; overflow-x: auto;}
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</head>
<body class="nav-sidebar docked nav-fixed">
<div id="quarto-search-results"></div>
<header id="quarto-header" class="headroom fixed-top">
<nav class="navbar navbar-expand " data-bs-theme="dark">
<div class="navbar-container container-fluid">
<div class="navbar-brand-container mx-auto">
<a class="navbar-brand" href="./index.html">
<span class="navbar-title">Axolotl</span>
</a>
</div>
<div class="quarto-navbar-tools tools-wide">
<a href="https://twitter.com/axolotl_ai" title="" class="quarto-navigation-tool px-1" aria-label=""><i class="bi bi-twitter"></i></a>
<a href="https://github.com/OpenAccess-AI-Collective/axolotl/" title="" class="quarto-navigation-tool px-1" aria-label=""><i class="bi bi-github"></i></a>
<a href="https://discord.gg/7m9sfhzaf3" title="" class="quarto-navigation-tool px-1" aria-label=""><i class="bi bi-discord"></i></a>
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<!-- sidebar -->
<nav id="quarto-sidebar" class="sidebar collapse collapse-horizontal quarto-sidebar-collapse-item sidebar-navigation docked overflow-auto">
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<li>Can you train StableLM with this? Yes, but only with a single GPU atm. Multi GPU support is coming soon! Just waiting on this <a href="https://github.com/huggingface/transformers/pull/22874">PR</a></li>
<li>Will this work with Deepspeed? Thats still a WIP, but setting <code>export ACCELERATE_USE_DEEPSPEED=true</code> should work in some cases</li>
<li><code>Error invalid argument at line 359 in file /workspace/bitsandbytes/csrc/pythonInterface.c</code> <code>/arrow/cpp/src/arrow/filesystem/s3fs.cc:2598: arrow::fs::FinalizeS3 was not called even though S3 was initialized.</code> This could lead to a segmentation fault at exit. Try reinstalling bitsandbytes and transformers from source.</li>
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el,
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});
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</div> <!-- /content -->
</body></html>

622
TODO.html Normal file
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<meta charset="utf-8">
<meta name="generator" content="quarto-1.4.533">
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
<title>Axolotl</title>
<style>
code{white-space: pre-wrap;}
span.smallcaps{font-variant: small-caps;}
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<div class="navbar-brand-container mx-auto">
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<span class="navbar-title">Axolotl</span>
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<i class="bi bi-layout-text-sidebar-reverse"></i>
</button>
<nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"></ol></nav>
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</a>
</div>
</nav>
</header>
<!-- content -->
<div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
<!-- sidebar -->
<nav id="quarto-sidebar" class="sidebar collapse collapse-horizontal quarto-sidebar-collapse-item sidebar-navigation docked overflow-auto">
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<ul class="list-unstyled mt-1">
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="./index.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">Home</span></a>
</div>
</li>
<li class="sidebar-item sidebar-item-section">
<div class="sidebar-item-container">
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<span class="menu-text">How-To Guides</span></a>
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<div class="sidebar-item-container">
<a href="./docs/debugging.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">Debugging</span></a>
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<li class="sidebar-item">
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<span class="menu-text">Multipack (Sample Packing)</span></a>
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<span class="menu-text">docs/fdsp_qlora.qmd</span>
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<li class="sidebar-item">
<div class="sidebar-item-container">
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<span class="menu-text">Template-free prompt construction</span></a>
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<div class="sidebar-item-container">
<a href="./docs/nccl.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">NCCL</span></a>
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</li>
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<a href="./docs/mac.html" class="sidebar-item-text sidebar-link">
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<a href="./docs/multi-node.html" class="sidebar-item-text sidebar-link">
<span class="menu-text">Multi Node</span></a>
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</li>
</ul>
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<i class="bi bi-chevron-right ms-2"></i>
</a>
</div>
<ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">
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<!-- margin-sidebar -->
<div id="quarto-margin-sidebar" class="sidebar margin-sidebar">
<nav id="TOC" role="doc-toc" class="toc-active">
<h2 id="toc-title">On this page</h2>
<ul>
<li><a href="#todo-list" id="toc-todo-list" class="nav-link active" data-scroll-target="#todo-list">todo list</a>
<ul class="collapse">
<li><a href="#things-that-are-known-not-to-work" id="toc-things-that-are-known-not-to-work" class="nav-link" data-scroll-target="#things-that-are-known-not-to-work">things that are known not to work</a></li>
</ul></li>
</ul>
</nav>
</div>
<!-- main -->
<main class="content" id="quarto-document-content">
<section id="todo-list" class="level1">
<h1>todo list</h1>
<ul>
<li>[] Validation of parameters for combinations that wont work</li>
</ul>
<section id="things-that-are-known-not-to-work" class="level2">
<h2 class="anchored" data-anchor-id="things-that-are-known-not-to-work">things that are known not to work</h2>
<ul>
<li>FSDP offload and gradient_checkpointing - https://github.com/pytorch/pytorch/issues/82203</li>
<li>adamw_bnb_8bit doesnt play well with FSDP offload</li>
</ul>
</section>
</section>
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How to debug Axolotl
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<p>This document provides some tips and tricks for debugging Axolotl. It also provides an example configuration for debugging with VSCode. A good debugging setup is essential to understanding how Axolotl code works behind the scenes.</p>
<section id="table-of-contents" class="level2">
<h2 class="anchored" data-anchor-id="table-of-contents">Table of Contents</h2>
<ul>
<li><a href="#general-tips">General Tips</a></li>
<li><a href="#debugging-with-vscode">Debugging with VSCode</a>
<ul>
<li><a href="#background">Background</a></li>
<li><a href="#configuration">Configuration</a></li>
<li><a href="#customizing-your-debugger">Customizing your debugger</a></li>
<li><a href="#video-tutorial">Video Tutorial</a></li>
</ul></li>
<li><a href="#debugging-with-docker">Debugging With Docker</a>
<ul>
<li><a href="#setup">Setup</a></li>
<li><a href="#attach-to-container">Attach To Container</a></li>
<li><a href="#video---attaching-to-docker-on-remote-host">Video - Attaching To Docker On Remote Host</a></li>
</ul></li>
</ul>
</section>
<section id="general-tips" class="level2">
<h2 class="anchored" data-anchor-id="general-tips">General Tips</h2>
<p>While debugging its helpful to simplify your test scenario as much as possible. Here are some tips for doing so:</p>
<blockquote class="blockquote">
<p>[!Important] All of these tips are incorporated into the <a href="#configuration">example configuration</a> for debugging with VSCode below.</p>
</blockquote>
<ol type="1">
<li><strong>Make sure you are using the latest version of axolotl</strong>: This project changes often and bugs get fixed fast. Check your git branch and make sure you have pulled the latest changes from <code>main</code>.</li>
<li><strong>Eliminate concurrency</strong>: Restrict the number of processes to 1 for both training and data preprocessing:
<ul>
<li>Set <code>CUDA_VISIBLE_DEVICES</code> to a single GPU, ex: <code>export CUDA_VISIBLE_DEVICES=0</code>.</li>
<li>Set <code>dataset_processes: 1</code> in your axolotl config or run the training command with <code>--dataset_processes=1</code>.</li>
</ul></li>
<li><strong>Use a small dataset</strong>: Construct or use a small dataset from HF Hub. When using a small dataset, you will often have to make sure <code>sample_packing: False</code> and <code>eval_sample_packing: False</code> to avoid errors. If you are in a pinch and dont have time to construct a small dataset but want to use from the HF Hub, you can shard the data (this will still tokenize the entire dataset, but will only use a fraction of the data for training. For example, to shard the dataset into 20 pieces, add the following to your axolotl config): <code>yaml dataset: ... shards: 20</code></li>
<li><strong>Use a small model</strong>: A good example of a small model is <a href="https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0">TinyLlama/TinyLlama-1.1B-Chat-v1.0</a>.</li>
<li><strong>Minimize iteration time</strong>: Make sure the training loop finishes as fast as possible, with these settings.
<ul>
<li><code>micro_batch_size: 1</code></li>
<li><code>max_steps: 1</code></li>
<li><code>val_set_size: 0</code></li>
</ul></li>
<li><strong>Clear Caches:</strong> Axolotl caches certain steps and so does the underlying HuggingFace trainer. You may want to clear some of these caches when debugging.
<ul>
<li>Data preprocessing: When debugging data preprocessing, which includes prompt template formation, you may want to delete the directory set in <code>dataset_prepared_path:</code> in your axolotl config. If you didnt set this value, the default is <code>last_run_prepared</code>.</li>
<li>HF Hub: If you are debugging data preprocessing, you should clear the relevant HF cache <a href="https://huggingface.co/docs/datasets/cache">HuggingFace cache</a>, by deleting the appropriate <code>~/.cache/huggingface/datasets/...</code> folder(s).</li>
<li><strong>The recommended approach is to redirect all outputs and caches to a temporary folder and delete selected subfolders before each run. This is demonstrated in the example configuration below.</strong></li>
</ul></li>
</ol>
</section>
<section id="debugging-with-vscode" class="level2">
<h2 class="anchored" data-anchor-id="debugging-with-vscode">Debugging with VSCode</h2>
<section id="background" class="level3">
<h3 class="anchored" data-anchor-id="background">Background</h3>
<p>The below example shows how to configure VSCode to debug data preprocessing of the <code>sharegpt</code> format. This is the format used when you have the following in your axolotl config:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">datasets</span><span class="kw">:</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> </span><span class="fu">path</span><span class="kw">:</span><span class="at"> &lt;path to your sharegpt formatted dataset&gt;</span><span class="co"> # example on HF Hub: philschmid/guanaco-sharegpt-style</span></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">type</span><span class="kw">:</span><span class="at"> sharegpt</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<blockquote class="blockquote">
<p>[!Important] If you are already familiar with advanced VSCode debugging, you can skip the below explanation and look at the files <a href="../.vscode/launch.json">.vscode/launch.json</a> and <a href="../.vscode/tasks.json">.vscode/tasks.json</a> for an example configuration.</p>
</blockquote>
<blockquote class="blockquote">
<p>[!Tip] If you prefer to watch a video, rather than read, you can skip to the <a href="#video-tutorial">video tutorial</a> below (but doing both is recommended).</p>
</blockquote>
</section>
<section id="setup" class="level3">
<h3 class="anchored" data-anchor-id="setup">Setup</h3>
<p>Make sure you have an <a href="https://setuptools.pypa.io/en/latest/userguide/development_mode.html">editable install</a> of Axolotl, which ensures that changes you make to the code are reflected at runtime. Run the following commands from the root of this project:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> install packaging</span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> install <span class="at">-e</span> <span class="st">'.[flash-attn,deepspeed]'</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<section id="remote-hosts" class="level4">
<h4 class="anchored" data-anchor-id="remote-hosts">Remote Hosts</h4>
<p>If you developing on a remote host, you can easily use VSCode to debug remotely. To do so, you will need to follow this <a href="https://code.visualstudio.com/docs/remote/ssh">remote - SSH guide</a>. You can also see the video below on <a href="#video---attaching-to-docker-on-remote-host">Docker and Remote SSH debugging</a>.</p>
</section>
</section>
<section id="configuration" class="level3">
<h3 class="anchored" data-anchor-id="configuration">Configuration</h3>
<p>The easiest way to get started is to modify the <a href="../.vscode/launch.json">.vscode/launch.json</a> file in this project. This is just an example configuration, so you may need to modify or copy it to suit your needs.</p>
<p>For example, to mimic the command <code>cd devtools &amp;&amp; CUDA_VISIBLE_DEVICES=0 accelerate launch -m axolotl.cli.train dev_sharegpt.yml</code>, you would use the below configuration<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>. Note that we add additional flags that override the axolotl config and incorporate the tips above (see the comments). We also set the working directory to <code>devtools</code> and set the <code>env</code> variable <code>HF_HOME</code> to a temporary folder that is later partially deleted. This is because we want to delete the HF dataset cache before each run in order to ensure that the data preprocessing code is run from scratch.</p>
<pre class="jsonc"><code>// .vscode/launch.json
{
"version": "0.2.0",
"configurations": [
{
"name": "Debug axolotl prompt - sharegpt",
"type": "python",
"module": "accelerate.commands.launch",
"request": "launch",
"args": [
"-m", "axolotl.cli.train", "dev_sharegpt.yml",
// The flags below simplify debugging by overriding the axolotl config
// with the debugging tips above. Modify as needed.
"--dataset_processes=1", // limits data preprocessing to one process
"--max_steps=1", // limits training to just one step
"--batch_size=1", // minimizes batch size
"--micro_batch_size=1", // minimizes batch size
"--val_set_size=0", // disables validation
"--sample_packing=False", // disables sample packing which is necessary for small datasets
"--eval_sample_packing=False",// disables sample packing on eval set
"--dataset_prepared_path=temp_debug/axolotl_outputs/data", // send data outputs to a temp folder
"--output_dir=temp_debug/axolotl_outputs/model" // send model outputs to a temp folder
],
"console": "integratedTerminal", // show output in the integrated terminal
"cwd": "${workspaceFolder}/devtools", // set working directory to devtools from the root of the project
"justMyCode": true, // step through only axolotl code
"env": {"CUDA_VISIBLE_DEVICES": "0", // Since we aren't doing distributed training, we need to limit to one GPU
"HF_HOME": "${workspaceFolder}/devtools/temp_debug/.hf-cache"}, // send HF cache to a temp folder
"preLaunchTask": "cleanup-for-dataprep", // delete temp folders (see below)
}
]
}</code></pre>
<p><strong>Additional notes about this configuration:</strong></p>
<ul>
<li>The argument <code>justMyCode</code> is set to <code>true</code> such that you step through only the axolotl code. If you want to step into dependencies, set this to <code>false</code>.</li>
<li>The <code>preLaunchTask</code>: <code>cleanup-for-dataprep</code> is defined in <a href="../.vscode/tasks.json">.vscode/tasks.json</a> and is used to delete the following folders before debugging, which is essential to ensure that the data pre-processing code is run from scratch:
<ul>
<li><code>./devtools/temp_debug/axolotl_outputs</code></li>
<li><code>./devtools/temp_debug/.hf-cache/datasets</code></li>
</ul></li>
</ul>
<blockquote class="blockquote">
<p>[!Tip] You may not want to delete these folders. For example, if you are debugging model training instead of data pre-processing, you may NOT want to delete the cache or output folders. You may also need to add additional tasks to the <code>tasks.json</code> file depending on your use case.</p>
</blockquote>
<p>Below is the <a href="../.vscode/tasks.json">./vscode/tasks.json</a> file that defines the <code>cleanup-for-dataprep</code> task. This task is run before each debugging session when you use the above configuration. Note how there are two tasks that delete the two folders mentioned above. The third task <code>cleanup-for-dataprep</code> is a composite task that combines the two tasks. A composite task is necessary because VSCode does not allow you to specify multiple tasks in the <code>preLaunchTask</code> argument of the <code>launch.json</code> file.</p>
<pre class="jsonc"><code>// .vscode/tasks.json
// this file is used by launch.json
{
"version": "2.0.0",
"tasks": [
// this task changes into the devtools directory and deletes the temp_debug/axolotl_outputs folder
{
"label": "delete-outputs",
"type": "shell",
"command": "rm -rf temp_debug/axolotl_outputs",
"options":{ "cwd": "${workspaceFolder}/devtools"},
"problemMatcher": []
},
// this task changes into the devtools directory and deletes the `temp_debug/.hf-cache/datasets` folder
{
"label": "delete-temp-hf-dataset-cache",
"type": "shell",
"command": "rm -rf temp_debug/.hf-cache/datasets",
"options":{ "cwd": "${workspaceFolder}/devtools"},
"problemMatcher": []
},
// this task combines the two tasks above
{
"label": "cleanup-for-dataprep",
"dependsOn": ["delete-outputs", "delete-temp-hf-dataset-cache"],
}
]
}</code></pre>
</section>
<section id="customizing-your-debugger" class="level3">
<h3 class="anchored" data-anchor-id="customizing-your-debugger">Customizing your debugger</h3>
<p>Your debugging use case may differ from the example above. The easiest thing to do is to put your own axolotl config in the <code>devtools</code> folder and modify the <code>launch.json</code> file to use your config. You may also want to modify the <code>preLaunchTask</code> to delete different folders or not delete anything at all.</p>
</section>
<section id="video-tutorial" class="level3">
<h3 class="anchored" data-anchor-id="video-tutorial">Video Tutorial</h3>
<p>The following video tutorial walks through the above configuration and demonstrates how to debug with VSCode, (click the image below to watch):</p>
<div style="text-align: center; line-height: 0;">
<p><a href="https://youtu.be/xUUB11yeMmc" target="_blank" title="How to debug Axolotl (for fine tuning LLMs)"><img src="https://i.ytimg.com/vi/xUUB11yeMmc/maxresdefault.jpg" style="border-radius: 10px; display: block; margin: auto;" width="560" height="315"></a></p>
<figcaption style="font-size: smaller;">
<a href="https://hamel.dev">Hamel Husains</a> tutorial: <a href="https://www.youtube.com/watch?v=xUUB11yeMmc">Debugging Axolotl w/VSCode</a>
</figcaption>
</div>
<p><br></p>
</section>
</section>
<section id="debugging-with-docker" class="level2">
<h2 class="anchored" data-anchor-id="debugging-with-docker">Debugging With Docker</h2>
<p>Using <a href="https://hub.docker.com/r/winglian/axolotl/tags">official Axolotl Docker images</a> is a great way to debug your code, and is a very popular way to use Axolotl. Attaching VSCode to Docker takes a few more steps.</p>
<section id="setup-1" class="level3">
<h3 class="anchored" data-anchor-id="setup-1">Setup</h3>
<p>On the host that is running axolotl (ex: if you are using a remote host), clone the axolotl repo and change your current directory to the root:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="fu">git</span> clone https://github.com/OpenAccess-AI-Collective/axolotl</span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a><span class="bu">cd</span> axolotl</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<blockquote class="blockquote">
<p>[!Tip] If you already have axolotl cloned on your host, make sure you have the latest changes and change into the root of the project.</p>
</blockquote>
<p>Next, run the desired docker image and mount the current directory. Below is a docker command you can run to do this:<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
<div class="sourceCode" id="cb6"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="ex">docker</span> run <span class="at">--privileged</span> <span class="at">--gpus</span> <span class="st">'"all"'</span> <span class="at">--shm-size</span> 10g <span class="at">--rm</span> <span class="at">-it</span> <span class="at">--name</span> axolotl <span class="at">--ipc</span><span class="op">=</span>host <span class="at">--ulimit</span> memlock=-1 <span class="at">--ulimit</span> stack=67108864 <span class="at">--mount</span> type=bind,src=<span class="st">"</span><span class="va">${PWD}</span><span class="st">"</span>,target=/workspace/axolotl <span class="at">-v</span> <span class="va">${HOME}</span>/.cache/huggingface:/root/.cache/huggingface winglian/axolotl:main-py3.10-cu118-2.0.1</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<blockquote class="blockquote">
<p>[!Tip] To understand which containers are available, see the <a href="../README.md#docker">Docker section of the README</a> and the <a href="https://hub.docker.com/r/winglian/axolotl/tags">DockerHub repo</a>. For details of how the Docker containers are built, see axolotls <a href="../.github/workflows/main.yml">Docker CI builds</a>.</p>
</blockquote>
<p>You will now be in the container. Next, perform an editable install of Axolotl:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> install packaging</span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> install <span class="at">-e</span> <span class="st">'.[flash-attn,deepspeed]'</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</section>
<section id="attach-to-container" class="level3">
<h3 class="anchored" data-anchor-id="attach-to-container">Attach To Container</h3>
<p>Next, if you are using a remote host, <a href="https://code.visualstudio.com/docs/remote/ssh">Remote into this host with VSCode</a>. If you are using a local host, you can skip this step.</p>
<p>Next, select <code>Dev Containers: Attach to Running Container...</code> using the command palette (<code>CMD + SHIFT + P</code>) in VSCode. You will be prompted to select a container to attach to. Select the container you just created. You will now be in the container with a working directory that is at the root of the project. Any changes you make to the code will be reflected both in the container and on the host.</p>
<p>Now you are ready to debug as described above (see <a href="#debugging-with-vscode">Debugging with VSCode</a>).</p>
</section>
<section id="video---attaching-to-docker-on-remote-host" class="level3">
<h3 class="anchored" data-anchor-id="video---attaching-to-docker-on-remote-host">Video - Attaching To Docker On Remote Host</h3>
<p>Here is a short video that demonstrates how to attach to a Docker container on a remote host:</p>
<div style="text-align: center; line-height: 0;">
<p><a href="https://youtu.be/0AuoR7QnHR0" target="_blank" title="Debugging Axolotl Part 2: Attaching to Docker on a Remote Host"><img src="https://i.ytimg.com/vi/0AuoR7QnHR0/hqdefault.jpg" style="border-radius: 10px; display: block; margin: auto;" width="560" height="315"></a></p>
<figcaption style="font-size: smaller;">
<a href="https://hamel.dev">Hamel Husains</a> tutorial: <a href="https://youtu.be/0AuoR7QnHR0">Debugging Axolotl Part 2: Attaching to Docker on a Remote Host </a>
</figcaption>
</div>
<p><br></p>
</section>
</section>
<div id="quarto-appendix" class="default"><section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes"><h2 class="anchored quarto-appendix-heading">Footnotes</h2>
<ol>
<li id="fn1"><p>The config actually mimics the command <code>CUDA_VISIBLE_DEVICES=0 python -m accelerate.commands.launch -m axolotl.cli.train devtools/sharegpt.yml</code>, but this is the same thing.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
<li id="fn2"><p>Many of the below flags are recommended best practices by Nvidia when using nvidia-container-toolkit. You can read more about these flags <a href="https://docs.nvidia.com/deeplearning/frameworks/user-guide/index.html">here</a>.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
</ol>
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<h1 class="title">FDSP + QLoRA</h1>
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Use FSDP with QLoRA to fine-tune large LLMs on consumer GPUs.
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<h2 class="anchored" data-anchor-id="background">Background</h2>
<p>Using FSDP with QLoRA is essential for <strong>fine-tuning larger (70b+ parameter) LLMs on consumer GPUs.</strong> For example, you can use FSDP + QLoRA to train a 70b model on two 24GB GPUs<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>.</p>
<p>Below, we describe how to use this feature in Axolotl.</p>
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<h2 class="anchored" data-anchor-id="usage">Usage</h2>
<p>To enable <code>QLoRA</code> with <code>FSDP</code>, you need to perform the following steps:</p>
<blockquote class="blockquote">
<p>![Tip] See the <a href="#example-config">example config</a> file in addition to reading these instructions.</p>
</blockquote>
<ol type="1">
<li>Set <code>adapter: qlora</code> in your axolotl config file.</li>
<li>Enable FSDP in your axolotl config, as <a href="https://github.com/OpenAccess-AI-Collective/axolotl?tab=readme-ov-file#fsdp">described here</a>.</li>
<li>Use one of the supported model types: <code>llama</code>, <code>mistral</code> or <code>mixtral</code>.</li>
</ol>
</section>
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<h2 class="anchored" data-anchor-id="example-config">Example Config</h2>
<p><a href="../examples/llama-2/qlora-fsdp.yml">examples/llama-2/qlora-fsdp.yml</a> contains an example of how to enable QLoRA + FSDP in axolotl.</p>
</section>
<section id="references" class="level2">
<h2 class="anchored" data-anchor-id="references">References</h2>
<ul>
<li><a href="https://github.com/OpenAccess-AI-Collective/axolotl/pull/1378">PR #1378</a> enabling QLoRA in FSDP in Axolotl.</li>
<li><a href="https://www.answer.ai/posts/2024-03-06-fsdp-qlora.html">Blog Post</a> from the <a href="https://www.answer.ai/">Answer.AI</a> team describing the work that enabled QLoRA in FSDP.</li>
<li>Related HuggingFace PRs Enabling FDSP + QLoRA:
<ul>
<li>Accelerate <a href="https://github.com/huggingface/accelerate/pull/2544">PR#2544</a></li>
<li>Transformers <a href="https://github.com/huggingface/transformers/pull/29587">PR#29587</a></li>
<li>TRL <a href="https://github.com/huggingface/trl/pull/1416">PR#1416</a></li>
<li>PEFT <a href="https://github.com/huggingface/peft/pull/1550">PR#1550</a></li>
</ul></li>
</ul>
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<div id="quarto-appendix" class="default"><section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes"><h2 class="anchored quarto-appendix-heading">Footnotes</h2>
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<li id="fn1"><p>This was enabled by <a href="https://www.answer.ai/posts/2024-03-06-fsdp-qlora.html">this work</a> from the Answer.AI team.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
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Use FSDP with QLoRA to fine-tune large LLMs on consumer GPUs.
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<h2 class="anchored" data-anchor-id="background">Background</h2>
<p>Using FSDP with QLoRA is essential for <strong>fine-tuning larger (70b+ parameter) LLMs on consumer GPUs.</strong> For example, you can use FSDP + QLoRA to train a 70b model on two 24GB GPUs<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>.</p>
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<p>To enable <code>QLoRA</code> with <code>FSDP</code>, you need to perform the following steps:</p>
<blockquote class="blockquote">
<p>![Tip] See the <a href="#example-config">example config</a> file in addition to reading these instructions.</p>
</blockquote>
<ol type="1">
<li>Set <code>adapter: qlora</code> in your axolotl config file.</li>
<li>Enable FSDP in your axolotl config, as <a href="https://github.com/OpenAccess-AI-Collective/axolotl?tab=readme-ov-file#fsdp">described here</a>.</li>
<li>Use one of the supported model types: <code>llama</code>, <code>mistral</code> or <code>mixtral</code>.</li>
</ol>
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<h2 class="anchored" data-anchor-id="example-config">Example Config</h2>
<p><a href="../examples/llama-2/qlora-fsdp.yml">examples/llama-2/qlora-fsdp.yml</a> contains an example of how to enable QLoRA + FSDP in axolotl.</p>
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<h2 class="anchored" data-anchor-id="references">References</h2>
<ul>
<li><a href="https://github.com/OpenAccess-AI-Collective/axolotl/pull/1378">PR #1378</a> enabling QLoRA in FSDP in Axolotl.</li>
<li><a href="https://www.answer.ai/posts/2024-03-06-fsdp-qlora.html">Blog Post</a> from the <a href="https://www.answer.ai/">Answer.AI</a> team describing the work that enabled QLoRA in FSDP.</li>
<li>Related HuggingFace PRs Enabling FDSP + QLoRA:
<ul>
<li>Accelerate <a href="https://github.com/huggingface/accelerate/pull/2544">PR#2544</a></li>
<li>Transformers <a href="https://github.com/huggingface/transformers/pull/29587">PR#29587</a></li>
<li>TRL <a href="https://github.com/huggingface/trl/pull/1416">PR#1416</a></li>
<li>PEFT <a href="https://github.com/huggingface/peft/pull/1550">PR#1550</a></li>
</ul></li>
</ul>
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<li id="fn1"><p>This was enabled by <a href="https://www.answer.ai/posts/2024-03-06-fsdp-qlora.html">this work</a> from the Answer.AI team.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
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<li><a href="#masking-inputs" id="toc-masking-inputs" class="nav-link" data-scroll-target="#masking-inputs">Masking Inputs</a></li>
<li><a href="#you-may-not-want-prompt-templates" id="toc-you-may-not-want-prompt-templates" class="nav-link" data-scroll-target="#you-may-not-want-prompt-templates">You may not want prompt templates</a></li>
<li><a href="#the-input_output-format" id="toc-the-input_output-format" class="nav-link" data-scroll-target="#the-input_output-format">The <code>input_output</code> format</a></li>
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<li><a href="#prepare-data" id="toc-prepare-data" class="nav-link" data-scroll-target="#prepare-data">1. Prepare Data</a></li>
<li><a href="#use-type-input_output" id="toc-use-type-input_output" class="nav-link" data-scroll-target="#use-type-input_output">2. Use <code>type: input_output</code></a></li>
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<h1 class="title">Template-free prompt construction</h1>
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Template-free prompt construction with the <code>input_output</code> format
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<ul>
<li><a href="#background">Background</a>
<ul>
<li><a href="#masking-inputs">Masking Inputs</a></li>
<li><a href="#you-may-not-want-prompt-templates">You may not want prompt templates</a></li>
<li><a href="#the-input_output-format">The <code>input_output</code> format</a></li>
</ul></li>
<li><a href="#usage">Usage</a>
<ul>
<li><a href="#1-prepare-data">1. Prepare Data</a></li>
<li><a href="#2-use-type-input_output">2. Use <code>type: input_output</code></a></li>
<li><a href="#3-check-the-prompts">3. Check the prompts</a></li>
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<!-- /TOC -->
<p><a id="markdown-background" name="background"></a></p>
<section id="background" class="level2">
<h2 class="anchored" data-anchor-id="background">Background</h2>
<p><a id="markdown-masking-inputs" name="masking-inputs"></a></p>
<section id="masking-inputs" class="level3">
<h3 class="anchored" data-anchor-id="masking-inputs">Masking Inputs</h3>
<p>One of the most popular features of <a href="https://github.com/OpenAccess-AI-Collective/axolotl">axolotl</a> is setting the following configuration value:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">train_on_inputs</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<p>If you declare a <a href="https://github.com/OpenAccess-AI-Collective/axolotl?tab=readme-ov-file#dataset">dataset formats</a> such as <code>alpaca</code> or <code>chatml</code>, axolotl knows what is an input (i.e.&nbsp;human) vs.&nbsp;an output (i.e.&nbsp;the assistant) and masks the input labels so that your model can focus on predicting the outputs only.</p>
<p><a id="markdown-you-may-not-want-prompt-templates" name="you-may-not-want-prompt-templates"></a></p>
</section>
<section id="you-may-not-want-prompt-templates" class="level3">
<h3 class="anchored" data-anchor-id="you-may-not-want-prompt-templates">You may not want prompt templates</h3>
<p>However, there are many situations where you dont want to use one of these formats or templates (I usually dont!). This is because they can:</p>
<ul>
<li>Add unnecessary boilerplate to your prompts.</li>
<li>Create artifacts like special delimiters <code>&lt;|im_start|&gt;</code> that can quickly become footguns if you dont include them correctly at inference time.</li>
<li>Enforce a <em>chat</em> interface when you do not want one. Sometimes you just want to fine-tune a model to a very specific task and do NOT want multi-turn conversations, roles, etc.</li>
<li>Limit you to only certain roles that the template allows.</li>
</ul>
<p><a id="markdown-the-inputoutput-format" name="the-inputoutput-format"></a></p>
</section>
<section id="the-input_output-format" class="level3">
<h3 class="anchored" data-anchor-id="the-input_output-format">The <code>input_output</code> format</h3>
<p>You can construct your prompts without a template by using the <code>input_output</code> format, by setting <code>type: input_output</code> in your configuration file like this:</p>
<p><strong>config.yml</strong></p>
<div class="sourceCode" id="cb2"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="fu">train_on_inputs</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span><span class="co"> # Mask segments of your data</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="fu">datasets</span><span class="kw">:</span></span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> </span><span class="fu">path</span><span class="kw">:</span><span class="at"> output.jsonl</span></span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">type</span><span class="kw">:</span><span class="at"> input_output</span><span class="co"> # use template free prompt construction</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<p>Unlike <code>type: completion</code>, which is also template-free, <code>type: input_output</code> allows you to mask segments of your text. More details on how this works are described below.</p>
<p><a id="markdown-usage" name="usage"></a></p>
</section>
</section>
<section id="usage" class="level2">
<h2 class="anchored" data-anchor-id="usage">Usage</h2>
<p>This is how you can use the <code>input_output</code> format:</p>
<p><a id="markdown-1-prepare-data" name="1-prepare-data"></a></p>
<section id="prepare-data" class="level3">
<h3 class="anchored" data-anchor-id="prepare-data">1. Prepare Data</h3>
<p>To use the <code>input_output</code> format, collect your data in the following format into a jsonl file (below is the first row from the file <code>output</code>.jsonl` pretty printed):</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="ex">$</span> head <span class="at">-n1</span> output.jsonl <span class="kw">|</span> <span class="ex">python</span> <span class="at">-m</span> json.tool</span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="ex">{.cell-output</span> .cell-output-stdout}</span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a> <span class="st">"segments"</span><span class="ex">:</span> [</span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> true,</span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"&lt;s&gt;Hello\n"</span></span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a> <span class="ex">},</span></span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> true,</span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"hi there!. "</span></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a> <span class="ex">},</span></span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb3-15"><a href="#cb3-15" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> false,</span>
<span id="cb3-16"><a href="#cb3-16" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"goodbye "</span></span>
<span id="cb3-17"><a href="#cb3-17" aria-hidden="true" tabindex="-1"></a> <span class="ex">},</span></span>
<span id="cb3-18"><a href="#cb3-18" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb3-19"><a href="#cb3-19" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> true,</span>
<span id="cb3-20"><a href="#cb3-20" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"farewell&lt;/s&gt;"</span></span>
<span id="cb3-21"><a href="#cb3-21" aria-hidden="true" tabindex="-1"></a> <span class="kw">}</span></span>
<span id="cb3-22"><a href="#cb3-22" aria-hidden="true" tabindex="-1"></a> <span class="ex">]</span></span>
<span id="cb3-23"><a href="#cb3-23" aria-hidden="true" tabindex="-1"></a> <span class="kw">}</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<p>Set <code>label:false</code> when you want to mask a segment of text so that the model isnt trained on it. Some things to keep in mind:</p>
<blockquote class="blockquote">
<p>[!IMPORTANT] 1. <strong>EOS, BOS, spaces, newlines etc. are entirely up to you. Axolotl concatenates all the segments as-is.</strong> The tokenizer doesnt add anything additional. Notice how I added spaces, newlines, <code>&lt;s&gt;</code> (BOS), and <code>&lt;/s&gt;</code> (EOS) myself. 2. Make sure you check the materialized output to validate that the prompt is getting assembled how you like.</p>
</blockquote>
<p><a id="markdown-2-use-type-inputoutput" name="2-use-type-inputoutput"></a></p>
</section>
<section id="use-type-input_output" class="level3">
<h3 class="anchored" data-anchor-id="use-type-input_output">2. Use <code>type: input_output</code></h3>
<p>Lets materialize data with our <code>output.jsonl</code> file by setting <code>type: input_output</code> in our axolotl config:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co"># training_config.yaml</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="fu">base_model</span><span class="kw">:</span><span class="at"> mistralai/Mistral-7B-v0.1</span></span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a><span class="fu">data_seed</span><span class="kw">:</span><span class="at"> </span><span class="dv">49</span></span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a><span class="fu">seed</span><span class="kw">:</span><span class="at"> </span><span class="dv">49</span></span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a><span class="fu">datasets</span><span class="kw">:</span></span>
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> </span><span class="fu">path</span><span class="kw">:</span><span class="at"> output.jsonl</span></span>
<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">type</span><span class="kw">:</span><span class="at"> input_output</span></span>
<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a><span class="fu">val_set_size</span><span class="kw">:</span><span class="at"> </span><span class="fl">0.1</span></span>
<span id="cb4-10"><a href="#cb4-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-11"><a href="#cb4-11" aria-hidden="true" tabindex="-1"></a><span class="fu">sequence_len</span><span class="kw">:</span><span class="at"> </span><span class="dv">896</span></span>
<span id="cb4-12"><a href="#cb4-12" aria-hidden="true" tabindex="-1"></a><span class="fu">sample_packing</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span>
<span id="cb4-13"><a href="#cb4-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-14"><a href="#cb4-14" aria-hidden="true" tabindex="-1"></a><span class="fu">micro_batch_size</span><span class="kw">:</span><span class="at"> </span><span class="dv">2</span></span>
<span id="cb4-15"><a href="#cb4-15" aria-hidden="true" tabindex="-1"></a><span class="fu">gradient_accumulation_steps</span><span class="kw">:</span><span class="at"> </span><span class="dv">3</span></span>
<span id="cb4-16"><a href="#cb4-16" aria-hidden="true" tabindex="-1"></a><span class="fu">eval_batch_size</span><span class="kw">:</span><span class="at"> </span><span class="dv">2</span></span>
<span id="cb4-17"><a href="#cb4-17" aria-hidden="true" tabindex="-1"></a><span class="fu">num_epochs</span><span class="kw">:</span><span class="at"> </span><span class="dv">1</span></span>
<span id="cb4-18"><a href="#cb4-18" aria-hidden="true" tabindex="-1"></a><span class="fu">learning_rate</span><span class="kw">:</span><span class="at"> </span><span class="fl">0.0002</span></span>
<span id="cb4-19"><a href="#cb4-19" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-20"><a href="#cb4-20" aria-hidden="true" tabindex="-1"></a><span class="fu">train_on_inputs</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span>
<span id="cb4-21"><a href="#cb4-21" aria-hidden="true" tabindex="-1"></a><span class="fu">special_tokens</span><span class="kw">:</span></span>
<span id="cb4-22"><a href="#cb4-22" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">bos_token</span><span class="kw">:</span><span class="at"> </span><span class="st">"&lt;s&gt;"</span></span>
<span id="cb4-23"><a href="#cb4-23" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">eos_token</span><span class="kw">:</span><span class="at"> </span><span class="st">"&lt;/s&gt;"</span></span>
<span id="cb4-24"><a href="#cb4-24" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">unk_token</span><span class="kw">:</span><span class="at"> </span><span class="st">"&lt;unk&gt;"</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<p>You can use the following command to materialize your data. The <code>--debug</code> flag will print the tokens, along with the labels so you can verify that the correct items are being ignored:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="ex">$</span> python <span class="at">-m</span> axolotl.cli.preprocess training_config.yaml <span class="at">--debug</span></span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a><span class="ex">...</span></span>
<span id="cb5-4"><a href="#cb5-4" aria-hidden="true" tabindex="-1"></a><span class="ex">[2024-03-05</span> 23:36:46,969] <span class="pp">[</span><span class="ss">INFO</span><span class="pp">]</span> <span class="pp">[</span><span class="ss">axolotl.check_example_labels:35</span><span class="pp">]</span> <span class="pp">[</span><span class="ss">PID:607731</span><span class="pp">]</span> <span class="pp">[</span><span class="ss">RANK:0</span><span class="pp">]</span> <span class="op">&lt;</span>s<span class="op">&gt;(</span><span class="ex">1,</span> 1<span class="op">)</span> Hello<span class="er">(</span><span class="ex">22557,</span> 22557<span class="kw">)</span></span>
<span id="cb5-5"><a href="#cb5-5" aria-hidden="true" tabindex="-1"></a><span class="kw">(</span><span class="ex">13,</span> 13<span class="kw">)</span> <span class="ex">hi</span><span class="er">(</span><span class="ex">12014,</span> 12014<span class="kw">)</span> <span class="ex">there</span><span class="er">(</span><span class="ex">736,</span> 736<span class="kw">)</span> <span class="ex">!</span><span class="er">(</span><span class="ex">28808,</span> 28808<span class="kw">)</span> <span class="bu">.</span><span class="er">(</span><span class="ex">28723,</span> 28723<span class="kw">)</span> <span class="kw">(</span><span class="ex">28705,</span> 28705<span class="kw">)</span> <span class="ex">good</span><span class="er">(</span><span class="ex">-100,</span> 1179<span class="kw">)</span> <span class="ex">bye</span><span class="er">(</span><span class="ex">-100,</span> 17664<span class="kw">)</span> <span class="kw">(</span><span class="ex">-100,</span> 28705<span class="kw">)</span> <span class="ex">fare</span><span class="er">(</span><span class="ex">19111,</span> 19111<span class="kw">)</span> <span class="ex">well</span><span class="er">(</span><span class="ex">5458,</span> 5458<span class="kw">)</span> <span class="op">&lt;</span>/s<span class="op">&gt;(</span><span class="ex">2,</span> 2<span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<p>The format is <code>decoded_token</code>(<code>label</code>, <code>token_id</code>), for example, <code>&lt;s&gt;(1, 1)</code> means that the token is <code>&lt;s&gt;</code>, the label is <code>1</code> and the token_id is <code>1</code>. When the label is <code>-100</code> then that token is ignored for training.</p>
<p><a id="markdown-3-check-the-prompts" name="3-check-the-prompts"></a></p>
</section>
<section id="check-the-prompts" class="level3">
<h3 class="anchored" data-anchor-id="check-the-prompts">3. Check the prompts</h3>
<p>Here is another way to check the materialized output:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> transformers <span class="im">import</span> AutoTokenizer</span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> datasets <span class="im">import</span> load_from_disk</span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> yaml</span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a>directory <span class="op">=</span> <span class="op">!</span>ls last_run_prepared<span class="op">/</span></span>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a><span class="cf">with</span> <span class="bu">open</span>(<span class="st">'training_config.yaml'</span>, <span class="st">'r'</span>) <span class="im">as</span> f:</span>
<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a> cfg <span class="op">=</span> yaml.safe_load(f)</span>
<span id="cb6-8"><a href="#cb6-8" aria-hidden="true" tabindex="-1"></a>model_id <span class="op">=</span> cfg[<span class="st">'base_model'</span>]</span>
<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a>tok <span class="op">=</span> AutoTokenizer.from_pretrained(model_id)</span>
<span id="cb6-10"><a href="#cb6-10" aria-hidden="true" tabindex="-1"></a>ds <span class="op">=</span> load_from_disk(<span class="ss">f'last_run_prepared/</span><span class="sc">{</span>directory[<span class="dv">0</span>]<span class="sc">}</span><span class="ss">/'</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="sourceCode" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="op">&gt;&gt;&gt;</span> row <span class="op">=</span> ds[<span class="dv">0</span>]</span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a><span class="op">&gt;&gt;&gt;</span> <span class="bu">print</span>(tok.decode(row[<span class="st">'input_ids'</span>]))</span>
<span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a><span class="op">&lt;</span>s<span class="op">&gt;</span> Hello</span>
<span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a> hi there<span class="op">!</span>. goodbye farewell<span class="op">&lt;/</span>s<span class="op">&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<p>We can check that the right tokens are ingored by comparing the labels to each token:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a>pd.DataFrame([{<span class="st">'token'</span>: tok.decode(i), <span class="st">'label'</span>: l, <span class="st">'id'</span>:i} <span class="cf">for</span> i,l <span class="kw">in</span></span>
<span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a> <span class="bu">zip</span>(row[<span class="st">'input_ids'</span>], row[<span class="st">'labels'</span>])])</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<table class="table">
<thead>
<tr class="header">
<th>token</th>
<th>label</th>
<th>id</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>0</td>
<td>&lt;s&gt;</td>
<td>1</td>
</tr>
<tr class="even">
<td>1</td>
<td>Hello</td>
<td>22557</td>
</tr>
<tr class="odd">
<td>2</td>
<td>\n</td>
<td>13</td>
</tr>
<tr class="even">
<td>3</td>
<td>hi</td>
<td>12014</td>
</tr>
<tr class="odd">
<td>4</td>
<td>there</td>
<td>736</td>
</tr>
<tr class="even">
<td>5</td>
<td>!</td>
<td>28808</td>
</tr>
<tr class="odd">
<td>6</td>
<td>.</td>
<td>28723</td>
</tr>
<tr class="even">
<td>7</td>
<td></td>
<td>28705</td>
</tr>
<tr class="odd">
<td>8</td>
<td>good</td>
<td>-100</td>
</tr>
<tr class="even">
<td>9</td>
<td>bye</td>
<td>-100</td>
</tr>
<tr class="odd">
<td>10</td>
<td></td>
<td>-100</td>
</tr>
<tr class="even">
<td>11</td>
<td>fare</td>
<td>19111</td>
</tr>
<tr class="odd">
<td>12</td>
<td>well</td>
<td>5458</td>
</tr>
<tr class="even">
<td>13</td>
<td>&lt;/s&gt;</td>
<td>2</td>
</tr>
</tbody>
</table>
<p>If we look at the input data, the above table seems correct! (The jsonl version is repeated below for reference):</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="ex">$</span> head <span class="at">-n1</span> output.jsonl <span class="kw">|</span> <span class="ex">python</span> <span class="at">-m</span> json.tool</span>
<span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a><span class="ex">{.cell-output</span> .cell-output-stdout}</span>
<span id="cb9-4"><a href="#cb9-4" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb9-5"><a href="#cb9-5" aria-hidden="true" tabindex="-1"></a> <span class="st">"segments"</span><span class="ex">:</span> [</span>
<span id="cb9-6"><a href="#cb9-6" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb9-7"><a href="#cb9-7" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> true,</span>
<span id="cb9-8"><a href="#cb9-8" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"&lt;s&gt;Hello\n"</span></span>
<span id="cb9-9"><a href="#cb9-9" aria-hidden="true" tabindex="-1"></a> <span class="ex">},</span></span>
<span id="cb9-10"><a href="#cb9-10" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb9-11"><a href="#cb9-11" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> true,</span>
<span id="cb9-12"><a href="#cb9-12" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"hi there!. "</span></span>
<span id="cb9-13"><a href="#cb9-13" aria-hidden="true" tabindex="-1"></a> <span class="ex">},</span></span>
<span id="cb9-14"><a href="#cb9-14" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb9-15"><a href="#cb9-15" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> false,</span>
<span id="cb9-16"><a href="#cb9-16" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"goodbye "</span></span>
<span id="cb9-17"><a href="#cb9-17" aria-hidden="true" tabindex="-1"></a> <span class="ex">},</span></span>
<span id="cb9-18"><a href="#cb9-18" aria-hidden="true" tabindex="-1"></a> <span class="kw">{</span></span>
<span id="cb9-19"><a href="#cb9-19" aria-hidden="true" tabindex="-1"></a> <span class="st">"label"</span><span class="ex">:</span> true,</span>
<span id="cb9-20"><a href="#cb9-20" aria-hidden="true" tabindex="-1"></a> <span class="st">"text"</span><span class="ex">:</span> <span class="st">"farewell&lt;/s&gt;"</span></span>
<span id="cb9-21"><a href="#cb9-21" aria-hidden="true" tabindex="-1"></a> <span class="kw">}</span></span>
<span id="cb9-22"><a href="#cb9-22" aria-hidden="true" tabindex="-1"></a> <span class="ex">]</span></span>
<span id="cb9-23"><a href="#cb9-23" aria-hidden="true" tabindex="-1"></a> <span class="kw">}</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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Mac M-series support
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<p>Currently Axolotl on Mac is partially usable, many of the dependencies of Axolotl including Pytorch do not support MPS or have incomplete support.</p>
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How to use Axolotl on multiple machines
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<p>You will need to create a configuration for accelerate, either by using <code>accelerate config</code> and follow the instructions or you can use one of the preset below:</p>
<p>~/.cache/huggingface/accelerate/default_config.yaml</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">compute_environment</span><span class="kw">:</span><span class="at"> LOCAL_MACHINE</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="fu">debug</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="fu">distributed_type</span><span class="kw">:</span><span class="at"> FSDP</span></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="fu">downcast_bf16</span><span class="kw">:</span><span class="at"> </span><span class="st">'no'</span></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="fu">machine_rank</span><span class="kw">:</span><span class="at"> </span><span class="dv">0</span><span class="co"> # Set to 0 for the main machine, increment by one for other machines</span></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="fu">main_process_ip</span><span class="kw">:</span><span class="at"> </span><span class="fl">10.0.0.4</span><span class="co"> # Set to main machine's IP</span></span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a><span class="fu">main_process_port</span><span class="kw">:</span><span class="at"> </span><span class="dv">5000</span></span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="fu">main_training_function</span><span class="kw">:</span><span class="at"> main</span></span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a><span class="fu">mixed_precision</span><span class="kw">:</span><span class="at"> bf16</span></span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a><span class="fu">num_machines</span><span class="kw">:</span><span class="at"> </span><span class="dv">2</span><span class="co"> # Change to the number of machines</span></span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a><span class="fu">num_processes</span><span class="kw">:</span><span class="at"> </span><span class="dv">4</span><span class="co"> # That's the total number of GPUs, (for example: if you have 2 machines with 4 GPU, put 8)</span></span>
<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a><span class="fu">rdzv_backend</span><span class="kw">:</span><span class="at"> static</span></span>
<span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a><span class="fu">same_network</span><span class="kw">:</span><span class="at"> </span><span class="ch">true</span></span>
<span id="cb1-14"><a href="#cb1-14" aria-hidden="true" tabindex="-1"></a><span class="fu">tpu_env</span><span class="kw">:</span><span class="at"> </span><span class="kw">[]</span></span>
<span id="cb1-15"><a href="#cb1-15" aria-hidden="true" tabindex="-1"></a><span class="fu">tpu_use_cluster</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span>
<span id="cb1-16"><a href="#cb1-16" aria-hidden="true" tabindex="-1"></a><span class="fu">tpu_use_sudo</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span>
<span id="cb1-17"><a href="#cb1-17" aria-hidden="true" tabindex="-1"></a><span class="fu">use_cpu</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<p>Configure your model to use FSDP with for example:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="fu">fsdp</span><span class="kw">:</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> full_shard</span></span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> auto_wrap</span></span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a><span class="fu">fsdp_config</span><span class="kw">:</span></span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">fsdp_offload_params</span><span class="kw">:</span><span class="at"> </span><span class="ch">true</span></span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">fsdp_state_dict_type</span><span class="kw">:</span><span class="at"> FULL_STATE_DICT</span></span>
<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">fsdp_transformer_layer_cls_to_wrap</span><span class="kw">:</span><span class="at"> LlamaDecoderLayer</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<section id="machine-configuration" class="level2">
<h2 class="anchored" data-anchor-id="machine-configuration">Machine configuration</h2>
<p>On each machine you need a copy of Axolotl, we suggest using the same commit to ensure compatibility.</p>
<p>You will also need to have the same configuration file for your model on each machine.</p>
<p>On the main machine only, make sure the port you set as <code>main_process_port</code> is open in TCP and reachable by other machines.</p>
<p>All you have to do now is launch using accelerate as you would usually do on each machine and voila, the processes will start once you have launched accelerate on every machine.</p>
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Multipack is a technique to pack multiple sequences into a single batch to increase training throughput.
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<h2 class="anchored" data-anchor-id="visualization-of-multipack-with-flash-attention">Visualization of Multipack with Flash Attention</h2>
<p>Because Flash Attention simply drops the attention mask, we do not need to construct a 4d attention mask. We only need to concatenate the sequences into a single batch and let flash attention know where each new sequence begins.</p>
<p>4k context, bsz =4, each character represents 256 tokens X represents a padding token</p>
<pre><code> 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5
[[ A A A A A A A A A A A ]
B B B B B B ]
C C C C C C C ]
D D D D ]]
[[ E E E E E E E E ]
[ F F F F ]
[ G G G ]
[ H H H H ]]
[[ I I I ]
[ J J J ]
[ K K K K K]
[ L L L ]]</code></pre>
<p>after padding to longest input in each step</p>
<pre><code> 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5
[[ A A A A A A A A A A A ]
B B B B B B X X X X X X ]
C C C C C C C X X X X ]
D D D D X X X X X X X ]]
[[ E E E E E E E E ]
[ F F F F X X X X ]
[ G G G X X X X X ]
[ H H H H X X X X ]]
[[ I I I X X ]
[ J J J X X ]
[ K K K K K ]
[ L L L X X ]]</code></pre>
<p>w packing ( note its the same effective number of tokens per step, but a true bsz of 1)</p>
<pre><code> 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5
[[ A A A A A A A A A A A B B B B B
B C C C C C C C D D D D E E E E
E E E E F F F F F G G G H H H H
I I I J J J J K K K K K L L L X ]]</code></pre>
<p>cu_seqlens: [[ 0, 11, 17, 24, 28, 36, 41 44, 48, 51, 55, 60, 64]]</p>
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<h2 class="anchored" data-anchor-id="multipack-without-flash-attention">Multipack without Flash Attention</h2>
<p>Multipack can still be achieved without Flash attention, but with lower packing efficiency as we are not able to join multiple batches into a single batch due to context length limits without flash attention. We can use either Pytorchs Scaled Dot Product Attention implementation or native Pytorch attention implementation along with <a href="https://github.com/huggingface/transformers/pull/27539">4d attention masks</a> to pack sequences together and avoid cross attention.</p>
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Troubleshooting NCCL issues
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<p>NVIDIA NCCL is a library to facilitate and optimize multi-GPU communication operations, such as broadcast, all-gather, reduce, all-reduce, etc. Broadly, NCCL configuration is highly environment-specific and is configured via several <a href="https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/env.html">environment variables</a>. A common NCCL-related problem occurs when a long-running operation times out causing the training process to abort:</p>
<pre class="text"><code>Watchdog caught collective operation timeout: WorkNCCL(SeqNum=42, OpType=ALLGATHER, Timeout(ms)=1800000) ran for 1806948 milliseconds before timing out.</code></pre>
<p>Often, this timeout will happen after 30 minutes (the default setting) and is accompanied by below-average power consumption with near 100% GPU utilization before the error is raised. Nvidia recommends <a href="https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/troubleshooting.html#pci-access-control-services-acs">disabling PCI access control services (ACS)</a> as a possible solution if this is available to you.</p>
<p>Forcing cross-GPU communication via <a href="https://en.wikipedia.org/wiki/NVLink">NVLink</a> may help without increasing timeouts. To verify that your configuration is leveraging NVLink run the following command:</p>
<pre class="shell"><code>nvidia-smi nvlink --status</code></pre>
<p>To force NCCL to use NVLink, simply set this in the environment:</p>
<pre class="shell"><code>export NCCL_P2P_LEVEL=NVL</code></pre>
<p>If NVLink is not available in your environment there are other options for <code>NCCL_P2P_LEVEL</code> in the table below:</p>
<table class="table">
<colgroup>
<col style="width: 56%">
<col style="width: 44%">
</colgroup>
<thead>
<tr class="header">
<th>NCCL_P2P_LEVEL</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>PIX</td>
<td>P2P data transfers through no more than a single PCIe bridge. Faster data transfer rates vs to paths involving multiple bridges, but slower compared to direct GPU-to-GPU communication.</td>
</tr>
<tr class="even">
<td>PXB</td>
<td>P2P data transfers through multiple PCIe bridges but not going through the PCIe Host Bridge; this path involves a complex routing process, potentially incurring a moderate level of latency.</td>
</tr>
<tr class="odd">
<td>PHB</td>
<td>P2P data transfers occur over the PCIe and through a PCIe Host Bridge, typically involving the CPU, which can facilitate direct memory access but might introduce additional latency compared to more direct paths (ex PIX, NVL)</td>
</tr>
</tbody>
</table>
<p>To validate that acceptable data transfer speeds exist for your training job, running <a href="https://github.com/NVIDIA/nccl-tests/blob/master/README.md">NCCL Tests</a> can help pinpoint bottlenecks, for example:</p>
<pre class="shell"><code>./build/all_reduce_perf -b 8 -e 128M -f 2 -g 3</code></pre>
<p>It can be useful when debugging NCCL communication timeouts to activate additional logging in both PyTorch and NCCL:</p>
<pre class="shell"><code>export NCCL_DEBUG=INFO
export NCCL_DEBUG_SUBSYS=ALL
export TORCH_DISTRIBUTED_DEBUG=INFO
export TORCHELASTIC_ERROR_FILE=/PATH/TO/torcherror.log</code></pre>
<p>Finally, if you believe your training job needs more time you can increase the timeout past 30 minutes by setting the <code>ddp_timeout</code> value in the Axolotl configuration. See <a href="https://pytorch.org/docs/stable/distributed.html#torch.distributed.init_process_group">PyTorch init_process_group</a> for documentation on this value.</p>
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Reinforcement Learning from Human Feedback is a method whereby a language model is optimized from data using human feedback.
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<h3 class="anchored" data-anchor-id="overview">Overview</h3>
<p>Reinforcement Learning from Human Feedback is a method whereby a language model is optimized from data using human feedback. Various methods include, but not limited to:</p>
<ul>
<li>Proximal Policy Optimization (PPO) (not yet supported in axolotl)</li>
<li>Direct Preference Optimization (DPO)</li>
<li>Identity Preference Optimization (IPO)</li>
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<blockquote class="blockquote">
<p>[!IMPORTANT] This is a BETA feature and many features are not fully implemented. You are encouraged to open new PRs to improve the integration and functionality.</p>
</blockquote>
<p>The various RL training methods are implemented in trl and wrapped via axolotl. Below are various examples with how you can use various preference datasets to train models that use ChatML</p>
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<h4 class="anchored" data-anchor-id="dpo">DPO</h4>
<div class="sourceCode" id="cb1"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">rl</span><span class="kw">:</span><span class="at"> dpo</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="fu">datasets</span><span class="kw">:</span></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> </span><span class="fu">path</span><span class="kw">:</span><span class="at"> Intel/orca_dpo_pairs</span></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">split</span><span class="kw">:</span><span class="at"> train</span></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">type</span><span class="kw">:</span><span class="at"> chatml.intel</span></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> </span><span class="fu">path</span><span class="kw">:</span><span class="at"> argilla/ultrafeedback-binarized-preferences</span></span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">split</span><span class="kw">:</span><span class="at"> train</span></span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">type</span><span class="kw">:</span><span class="at"> chatml.argilla</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</section>
<section id="ipo" class="level4">
<h4 class="anchored" data-anchor-id="ipo">IPO</h4>
<div class="sourceCode" id="cb2"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="fu">rl</span><span class="kw">:</span><span class="at"> ipo</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</section>
<section id="orpo" class="level4">
<h4 class="anchored" data-anchor-id="orpo">ORPO</h4>
<p>Paper: https://arxiv.org/abs/2403.07691</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="fu">rl</span><span class="kw">:</span><span class="at"> orpo</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="fu">orpo_alpha</span><span class="kw">:</span><span class="at"> </span><span class="fl">0.1</span></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="fu">remove_unused_columns</span><span class="kw">:</span><span class="at"> </span><span class="ch">false</span></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a><span class="fu">chat_template</span><span class="kw">:</span><span class="at"> chatml</span></span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a><span class="fu">datasets</span><span class="kw">:</span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> </span><span class="fu">path</span><span class="kw">:</span><span class="at"> argilla/ultrafeedback-binarized-preferences-cleaned</span></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">type</span><span class="kw">:</span><span class="at"> orpo.chat_template</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</section>
<section id="using-local-dataset-files" class="level4">
<h4 class="anchored" data-anchor-id="using-local-dataset-files">Using local dataset files</h4>
<div class="sourceCode" id="cb4"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="fu">datasets</span><span class="kw">:</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> </span><span class="fu">ds_type</span><span class="kw">:</span><span class="at"> json</span></span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">data_files</span><span class="kw">:</span></span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="kw">-</span><span class="at"> orca_rlhf.jsonl</span></span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">split</span><span class="kw">:</span><span class="at"> train</span></span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a><span class="at"> </span><span class="fu">type</span><span class="kw">:</span><span class="at"> chatml.intel</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</section>
<section id="trl-autounwrap-for-peft" class="level4">
<h4 class="anchored" data-anchor-id="trl-autounwrap-for-peft">Trl autounwrap for peft</h4>
<p>Trl supports autounwrapping peft models, so that a ref model does not need to be additionally loaded, leading to less VRAM needed. This is on by default. To turn it off, pass the following config.</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode yaml code-with-copy"><code class="sourceCode yaml"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="co"># load ref model when adapter training.</span></span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a><span class="fu">rl_adapter_ref_model</span><span class="kw">:</span><span class="at"> </span><span class="ch">true</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<li><a href="#install-axolotl-and-dependencies" id="toc-install-axolotl-and-dependencies" class="nav-link" data-scroll-target="#install-axolotl-and-dependencies">Install Axolotl and dependencies</a></li>
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<h1 class="title">Example notebook for running Axolotl on google colab</h1>
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<section id="example-notebook-for-running-axolotl-on-google-colab" class="level1">
<h1>Example notebook for running Axolotl on google colab</h1>
<div id="cell-1" class="cell">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> torch</span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="co"># Check so there is a gpu available, a T4(free tier) is enough to run this notebook</span></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="cf">assert</span> (torch.cuda.is_available()<span class="op">==</span><span class="va">True</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<section id="install-axolotl-and-dependencies" class="level2">
<h2 class="anchored" data-anchor-id="install-axolotl-and-dependencies">Install Axolotl and dependencies</h2>
<div id="cell-3" class="cell" data-outputid="e3777b5a-40ef-424f-e181-62dfecd1dd01">
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="op">!</span>pip install torch<span class="op">==</span><span class="st">"2.1.2"</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="op">!</span>pip install <span class="op">-</span>e git<span class="op">+</span>https:<span class="op">//</span>github.com<span class="op">/</span>OpenAccess<span class="op">-</span>AI<span class="op">-</span>Collective<span class="op">/</span>axolotl<span class="co">#egg=axolotl</span></span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a><span class="op">!</span>pip install flash<span class="op">-</span>attn<span class="op">==</span><span class="st">"2.5.0"</span></span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a><span class="op">!</span>pip install deepspeed<span class="op">==</span><span class="st">"0.13.1"</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<section id="create-an-yaml-config-file" class="level2">
<h2 class="anchored" data-anchor-id="create-an-yaml-config-file">Create an yaml config file</h2>
<div id="cell-5" class="cell">
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> yaml</span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Your YAML string</span></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a>yaml_string <span class="op">=</span> <span class="st">"""</span></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a><span class="st">base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T</span></span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a><span class="st">model_type: LlamaForCausalLM</span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a><span class="st">tokenizer_type: LlamaTokenizer</span></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a><span class="st">is_llama_derived_model: true</span></span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a><span class="st">load_in_8bit: false</span></span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a><span class="st">load_in_4bit: true</span></span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a><span class="st">strict: false</span></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a><span class="st">datasets:</span></span>
<span id="cb3-15"><a href="#cb3-15" aria-hidden="true" tabindex="-1"></a><span class="st"> - path: mhenrichsen/alpaca_2k_test</span></span>
<span id="cb3-16"><a href="#cb3-16" aria-hidden="true" tabindex="-1"></a><span class="st"> type: alpaca</span></span>
<span id="cb3-17"><a href="#cb3-17" aria-hidden="true" tabindex="-1"></a><span class="st">dataset_prepared_path:</span></span>
<span id="cb3-18"><a href="#cb3-18" aria-hidden="true" tabindex="-1"></a><span class="st">val_set_size: 0.05</span></span>
<span id="cb3-19"><a href="#cb3-19" aria-hidden="true" tabindex="-1"></a><span class="st">output_dir: ./qlora-out</span></span>
<span id="cb3-20"><a href="#cb3-20" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-21"><a href="#cb3-21" aria-hidden="true" tabindex="-1"></a><span class="st">adapter: qlora</span></span>
<span id="cb3-22"><a href="#cb3-22" aria-hidden="true" tabindex="-1"></a><span class="st">lora_model_dir:</span></span>
<span id="cb3-23"><a href="#cb3-23" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-24"><a href="#cb3-24" aria-hidden="true" tabindex="-1"></a><span class="st">sequence_len: 1096</span></span>
<span id="cb3-25"><a href="#cb3-25" aria-hidden="true" tabindex="-1"></a><span class="st">sample_packing: true</span></span>
<span id="cb3-26"><a href="#cb3-26" aria-hidden="true" tabindex="-1"></a><span class="st">pad_to_sequence_len: true</span></span>
<span id="cb3-27"><a href="#cb3-27" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-28"><a href="#cb3-28" aria-hidden="true" tabindex="-1"></a><span class="st">lora_r: 32</span></span>
<span id="cb3-29"><a href="#cb3-29" aria-hidden="true" tabindex="-1"></a><span class="st">lora_alpha: 16</span></span>
<span id="cb3-30"><a href="#cb3-30" aria-hidden="true" tabindex="-1"></a><span class="st">lora_dropout: 0.05</span></span>
<span id="cb3-31"><a href="#cb3-31" aria-hidden="true" tabindex="-1"></a><span class="st">lora_target_modules:</span></span>
<span id="cb3-32"><a href="#cb3-32" aria-hidden="true" tabindex="-1"></a><span class="st">lora_target_linear: true</span></span>
<span id="cb3-33"><a href="#cb3-33" aria-hidden="true" tabindex="-1"></a><span class="st">lora_fan_in_fan_out:</span></span>
<span id="cb3-34"><a href="#cb3-34" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-35"><a href="#cb3-35" aria-hidden="true" tabindex="-1"></a><span class="st">wandb_project:</span></span>
<span id="cb3-36"><a href="#cb3-36" aria-hidden="true" tabindex="-1"></a><span class="st">wandb_entity:</span></span>
<span id="cb3-37"><a href="#cb3-37" aria-hidden="true" tabindex="-1"></a><span class="st">wandb_watch:</span></span>
<span id="cb3-38"><a href="#cb3-38" aria-hidden="true" tabindex="-1"></a><span class="st">wandb_name:</span></span>
<span id="cb3-39"><a href="#cb3-39" aria-hidden="true" tabindex="-1"></a><span class="st">wandb_log_model:</span></span>
<span id="cb3-40"><a href="#cb3-40" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-41"><a href="#cb3-41" aria-hidden="true" tabindex="-1"></a><span class="st">mlflow_experiment_name: colab-example</span></span>
<span id="cb3-42"><a href="#cb3-42" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-43"><a href="#cb3-43" aria-hidden="true" tabindex="-1"></a><span class="st">gradient_accumulation_steps: 1</span></span>
<span id="cb3-44"><a href="#cb3-44" aria-hidden="true" tabindex="-1"></a><span class="st">micro_batch_size: 1</span></span>
<span id="cb3-45"><a href="#cb3-45" aria-hidden="true" tabindex="-1"></a><span class="st">num_epochs: 4</span></span>
<span id="cb3-46"><a href="#cb3-46" aria-hidden="true" tabindex="-1"></a><span class="st">max_steps: 20</span></span>
<span id="cb3-47"><a href="#cb3-47" aria-hidden="true" tabindex="-1"></a><span class="st">optimizer: paged_adamw_32bit</span></span>
<span id="cb3-48"><a href="#cb3-48" aria-hidden="true" tabindex="-1"></a><span class="st">lr_scheduler: cosine</span></span>
<span id="cb3-49"><a href="#cb3-49" aria-hidden="true" tabindex="-1"></a><span class="st">learning_rate: 0.0002</span></span>
<span id="cb3-50"><a href="#cb3-50" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-51"><a href="#cb3-51" aria-hidden="true" tabindex="-1"></a><span class="st">train_on_inputs: false</span></span>
<span id="cb3-52"><a href="#cb3-52" aria-hidden="true" tabindex="-1"></a><span class="st">group_by_length: false</span></span>
<span id="cb3-53"><a href="#cb3-53" aria-hidden="true" tabindex="-1"></a><span class="st">bf16: false</span></span>
<span id="cb3-54"><a href="#cb3-54" aria-hidden="true" tabindex="-1"></a><span class="st">fp16: true</span></span>
<span id="cb3-55"><a href="#cb3-55" aria-hidden="true" tabindex="-1"></a><span class="st">tf32: false</span></span>
<span id="cb3-56"><a href="#cb3-56" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-57"><a href="#cb3-57" aria-hidden="true" tabindex="-1"></a><span class="st">gradient_checkpointing: true</span></span>
<span id="cb3-58"><a href="#cb3-58" aria-hidden="true" tabindex="-1"></a><span class="st">early_stopping_patience:</span></span>
<span id="cb3-59"><a href="#cb3-59" aria-hidden="true" tabindex="-1"></a><span class="st">resume_from_checkpoint:</span></span>
<span id="cb3-60"><a href="#cb3-60" aria-hidden="true" tabindex="-1"></a><span class="st">local_rank:</span></span>
<span id="cb3-61"><a href="#cb3-61" aria-hidden="true" tabindex="-1"></a><span class="st">logging_steps: 1</span></span>
<span id="cb3-62"><a href="#cb3-62" aria-hidden="true" tabindex="-1"></a><span class="st">xformers_attention:</span></span>
<span id="cb3-63"><a href="#cb3-63" aria-hidden="true" tabindex="-1"></a><span class="st">flash_attention: false</span></span>
<span id="cb3-64"><a href="#cb3-64" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-65"><a href="#cb3-65" aria-hidden="true" tabindex="-1"></a><span class="st">warmup_steps: 10</span></span>
<span id="cb3-66"><a href="#cb3-66" aria-hidden="true" tabindex="-1"></a><span class="st">evals_per_epoch:</span></span>
<span id="cb3-67"><a href="#cb3-67" aria-hidden="true" tabindex="-1"></a><span class="st">saves_per_epoch:</span></span>
<span id="cb3-68"><a href="#cb3-68" aria-hidden="true" tabindex="-1"></a><span class="st">debug:</span></span>
<span id="cb3-69"><a href="#cb3-69" aria-hidden="true" tabindex="-1"></a><span class="st">deepspeed:</span></span>
<span id="cb3-70"><a href="#cb3-70" aria-hidden="true" tabindex="-1"></a><span class="st">weight_decay: 0.0</span></span>
<span id="cb3-71"><a href="#cb3-71" aria-hidden="true" tabindex="-1"></a><span class="st">fsdp:</span></span>
<span id="cb3-72"><a href="#cb3-72" aria-hidden="true" tabindex="-1"></a><span class="st">fsdp_config:</span></span>
<span id="cb3-73"><a href="#cb3-73" aria-hidden="true" tabindex="-1"></a><span class="st">special_tokens:</span></span>
<span id="cb3-74"><a href="#cb3-74" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-75"><a href="#cb3-75" aria-hidden="true" tabindex="-1"></a><span class="st">"""</span></span>
<span id="cb3-76"><a href="#cb3-76" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-77"><a href="#cb3-77" aria-hidden="true" tabindex="-1"></a><span class="co"># Convert the YAML string to a Python dictionary</span></span>
<span id="cb3-78"><a href="#cb3-78" aria-hidden="true" tabindex="-1"></a>yaml_dict <span class="op">=</span> yaml.safe_load(yaml_string)</span>
<span id="cb3-79"><a href="#cb3-79" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-80"><a href="#cb3-80" aria-hidden="true" tabindex="-1"></a><span class="co"># Specify your file path</span></span>
<span id="cb3-81"><a href="#cb3-81" aria-hidden="true" tabindex="-1"></a>file_path <span class="op">=</span> <span class="st">'test_axolotl.yaml'</span></span>
<span id="cb3-82"><a href="#cb3-82" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-83"><a href="#cb3-83" aria-hidden="true" tabindex="-1"></a><span class="co"># Write the YAML file</span></span>
<span id="cb3-84"><a href="#cb3-84" aria-hidden="true" tabindex="-1"></a><span class="cf">with</span> <span class="bu">open</span>(file_path, <span class="st">'w'</span>) <span class="im">as</span> <span class="bu">file</span>:</span>
<span id="cb3-85"><a href="#cb3-85" aria-hidden="true" tabindex="-1"></a> yaml.dump(yaml_dict, <span class="bu">file</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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</section>
<section id="launch-the-training" class="level2">
<h2 class="anchored" data-anchor-id="launch-the-training">Launch the training</h2>
<div id="cell-7" class="cell" data-outputid="d6d0df17-4b53-439c-c802-22c0456d301b">
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Buy using the ! the comand will be executed as a bash command</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="op">!</span>accelerate launch <span class="op">-</span>m axolotl.cli.train <span class="op">/</span>content<span class="op">/</span>test_axolotl.yaml</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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</section>
<section id="play-with-inference" class="level2">
<h2 class="anchored" data-anchor-id="play-with-inference">Play with inference</h2>
<div id="cell-9" class="cell">
<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Buy using the ! the comand will be executed as a bash command</span></span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a><span class="op">!</span>accelerate launch <span class="op">-</span>m axolotl.cli.inference <span class="op">/</span>content<span class="op">/</span>test_axolotl.yaml <span class="op">\</span></span>
<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a> <span class="op">--</span>qlora_model_dir<span class="op">=</span><span class="st">"./qlora-out"</span> <span class="op">--</span>gradio</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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customClass: "code-copy-button-tooltip",
offset: [0, -8]});
tooltip.show();
}
setTimeout(function() {
if (tooltip) {
tooltip.hide();
button.removeAttribute("data-bs-title");
button.removeAttribute("data-bs-toggle");
button.removeAttribute("data-bs-placement");
}
button.setAttribute("title", currentTitle);
button.classList.remove('code-copy-button-checked');
}, 1000);
// clear code selection
e.clearSelection();
});
function tippyHover(el, contentFn, onTriggerFn, onUntriggerFn) {
const config = {
allowHTML: true,
maxWidth: 500,
delay: 100,
arrow: false,
appendTo: function(el) {
return el.parentElement;
},
interactive: true,
interactiveBorder: 10,
theme: 'quarto',
placement: 'bottom-start',
};
if (contentFn) {
config.content = contentFn;
}
if (onTriggerFn) {
config.onTrigger = onTriggerFn;
}
if (onUntriggerFn) {
config.onUntrigger = onUntriggerFn;
}
window.tippy(el, config);
}
const noterefs = window.document.querySelectorAll('a[role="doc-noteref"]');
for (var i=0; i<noterefs.length; i++) {
const ref = noterefs[i];
tippyHover(ref, function() {
// use id or data attribute instead here
let href = ref.getAttribute('data-footnote-href') || ref.getAttribute('href');
try { href = new URL(href).hash; } catch {}
const id = href.replace(/^#\/?/, "");
const note = window.document.getElementById(id);
return note.innerHTML;
});
}
const xrefs = window.document.querySelectorAll('a.quarto-xref');
const processXRef = (id, note) => {
// Strip column container classes
const stripColumnClz = (el) => {
el.classList.remove("page-full", "page-columns");
if (el.children) {
for (const child of el.children) {
stripColumnClz(child);
}
}
}
stripColumnClz(note)
if (id === null || id.startsWith('sec-')) {
// Special case sections, only their first couple elements
const container = document.createElement("div");
if (note.children && note.children.length > 2) {
container.appendChild(note.children[0].cloneNode(true));
for (let i = 1; i < note.children.length; i++) {
const child = note.children[i];
if (child.tagName === "P" && child.innerText === "") {
continue;
} else {
container.appendChild(child.cloneNode(true));
break;
}
}
if (window.Quarto?.typesetMath) {
window.Quarto.typesetMath(container);
}
return container.innerHTML
} else {
if (window.Quarto?.typesetMath) {
window.Quarto.typesetMath(note);
}
return note.innerHTML;
}
} else {
// Remove any anchor links if they are present
const anchorLink = note.querySelector('a.anchorjs-link');
if (anchorLink) {
anchorLink.remove();
}
if (window.Quarto?.typesetMath) {
window.Quarto.typesetMath(note);
}
return note.innerHTML;
}
}
for (var i=0; i<xrefs.length; i++) {
const xref = xrefs[i];
tippyHover(xref, undefined, function(instance) {
instance.disable();
let url = xref.getAttribute('href');
let hash = undefined;
if (url.startsWith('#')) {
hash = url;
} else {
try { hash = new URL(url).hash; } catch {}
}
if (hash) {
const id = hash.replace(/^#\/?/, "");
const note = window.document.getElementById(id);
if (note !== null) {
try {
const html = processXRef(id, note.cloneNode(true));
instance.setContent(html);
} finally {
instance.enable();
instance.show();
}
} else {
// See if we can fetch this
fetch(url.split('#')[0])
.then(res => res.text())
.then(html => {
const parser = new DOMParser();
const htmlDoc = parser.parseFromString(html, "text/html");
const note = htmlDoc.getElementById(id);
if (note !== null) {
const html = processXRef(id, note);
instance.setContent(html);
}
}).finally(() => {
instance.enable();
instance.show();
});
}
} else {
// See if we can fetch a full url (with no hash to target)
// This is a special case and we should probably do some content thinning / targeting
fetch(url)
.then(res => res.text())
.then(html => {
const parser = new DOMParser();
const htmlDoc = parser.parseFromString(html, "text/html");
const note = htmlDoc.querySelector('main.content');
if (note !== null) {
// This should only happen for chapter cross references
// (since there is no id in the URL)
// remove the first header
if (note.children.length > 0 && note.children[0].tagName === "HEADER") {
note.children[0].remove();
}
const html = processXRef(null, note);
instance.setContent(html);
}
}).finally(() => {
instance.enable();
instance.show();
});
}
}, function(instance) {
});
}
let selectedAnnoteEl;
const selectorForAnnotation = ( cell, annotation) => {
let cellAttr = 'data-code-cell="' + cell + '"';
let lineAttr = 'data-code-annotation="' + annotation + '"';
const selector = 'span[' + cellAttr + '][' + lineAttr + ']';
return selector;
}
const selectCodeLines = (annoteEl) => {
const doc = window.document;
const targetCell = annoteEl.getAttribute("data-target-cell");
const targetAnnotation = annoteEl.getAttribute("data-target-annotation");
const annoteSpan = window.document.querySelector(selectorForAnnotation(targetCell, targetAnnotation));
const lines = annoteSpan.getAttribute("data-code-lines").split(",");
const lineIds = lines.map((line) => {
return targetCell + "-" + line;
})
let top = null;
let height = null;
let parent = null;
if (lineIds.length > 0) {
//compute the position of the single el (top and bottom and make a div)
const el = window.document.getElementById(lineIds[0]);
top = el.offsetTop;
height = el.offsetHeight;
parent = el.parentElement.parentElement;
if (lineIds.length > 1) {
const lastEl = window.document.getElementById(lineIds[lineIds.length - 1]);
const bottom = lastEl.offsetTop + lastEl.offsetHeight;
height = bottom - top;
}
if (top !== null && height !== null && parent !== null) {
// cook up a div (if necessary) and position it
let div = window.document.getElementById("code-annotation-line-highlight");
if (div === null) {
div = window.document.createElement("div");
div.setAttribute("id", "code-annotation-line-highlight");
div.style.position = 'absolute';
parent.appendChild(div);
}
div.style.top = top - 2 + "px";
div.style.height = height + 4 + "px";
div.style.left = 0;
let gutterDiv = window.document.getElementById("code-annotation-line-highlight-gutter");
if (gutterDiv === null) {
gutterDiv = window.document.createElement("div");
gutterDiv.setAttribute("id", "code-annotation-line-highlight-gutter");
gutterDiv.style.position = 'absolute';
const codeCell = window.document.getElementById(targetCell);
const gutter = codeCell.querySelector('.code-annotation-gutter');
gutter.appendChild(gutterDiv);
}
gutterDiv.style.top = top - 2 + "px";
gutterDiv.style.height = height + 4 + "px";
}
selectedAnnoteEl = annoteEl;
}
};
const unselectCodeLines = () => {
const elementsIds = ["code-annotation-line-highlight", "code-annotation-line-highlight-gutter"];
elementsIds.forEach((elId) => {
const div = window.document.getElementById(elId);
if (div) {
div.remove();
}
});
selectedAnnoteEl = undefined;
};
// Handle positioning of the toggle
window.addEventListener(
"resize",
throttle(() => {
elRect = undefined;
if (selectedAnnoteEl) {
selectCodeLines(selectedAnnoteEl);
}
}, 10)
);
function throttle(fn, ms) {
let throttle = false;
let timer;
return (...args) => {
if(!throttle) { // first call gets through
fn.apply(this, args);
throttle = true;
} else { // all the others get throttled
if(timer) clearTimeout(timer); // cancel #2
timer = setTimeout(() => {
fn.apply(this, args);
timer = throttle = false;
}, ms);
}
};
}
// Attach click handler to the DT
const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');
for (const annoteDlNode of annoteDls) {
annoteDlNode.addEventListener('click', (event) => {
const clickedEl = event.target;
if (clickedEl !== selectedAnnoteEl) {
unselectCodeLines();
const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active');
if (activeEl) {
activeEl.classList.remove('code-annotation-active');
}
selectCodeLines(clickedEl);
clickedEl.classList.add('code-annotation-active');
} else {
// Unselect the line
unselectCodeLines();
clickedEl.classList.remove('code-annotation-active');
}
});
}
const findCites = (el) => {
const parentEl = el.parentElement;
if (parentEl) {
const cites = parentEl.dataset.cites;
if (cites) {
return {
el,
cites: cites.split(' ')
};
} else {
return findCites(el.parentElement)
}
} else {
return undefined;
}
};
var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
for (var i=0; i<bibliorefs.length; i++) {
const ref = bibliorefs[i];
const citeInfo = findCites(ref);
if (citeInfo) {
tippyHover(citeInfo.el, function() {
var popup = window.document.createElement('div');
citeInfo.cites.forEach(function(cite) {
var citeDiv = window.document.createElement('div');
citeDiv.classList.add('hanging-indent');
citeDiv.classList.add('csl-entry');
var biblioDiv = window.document.getElementById('ref-' + cite);
if (biblioDiv) {
citeDiv.innerHTML = biblioDiv.innerHTML;
}
popup.appendChild(citeDiv);
});
return popup.innerHTML;
});
}
}
});
</script>
</div> <!-- /content -->
</body></html>

View File

@@ -0,0 +1,76 @@
base_model: NousResearch/Llama-2-7b-hf
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: yahma/alpaca-cleaned
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./qlora-out
adapter: qlora
lora_model_dir:
sequence_len: 512
sample_packing: false
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 4
num_epochs: 4
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.00001
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
- full_shard
fsdp_config:
fsdp_limit_all_gathers: true
fsdp_sync_module_states: true
fsdp_offload_params: true
fsdp_use_orig_params: false
fsdp_cpu_ram_efficient_loading: true
fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
fsdp_state_dict_type: SHARDED_STATE_DICT
special_tokens:

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/* quarto syntax highlight colors */
:root {
--quarto-hl-ot-color: #003B4F;
--quarto-hl-at-color: #657422;
--quarto-hl-ss-color: #20794D;
--quarto-hl-an-color: #5E5E5E;
--quarto-hl-fu-color: #4758AB;
--quarto-hl-st-color: #20794D;
--quarto-hl-cf-color: #003B4F;
--quarto-hl-op-color: #5E5E5E;
--quarto-hl-er-color: #AD0000;
--quarto-hl-bn-color: #AD0000;
--quarto-hl-al-color: #AD0000;
--quarto-hl-va-color: #111111;
--quarto-hl-bu-color: inherit;
--quarto-hl-ex-color: inherit;
--quarto-hl-pp-color: #AD0000;
--quarto-hl-in-color: #5E5E5E;
--quarto-hl-vs-color: #20794D;
--quarto-hl-wa-color: #5E5E5E;
--quarto-hl-do-color: #5E5E5E;
--quarto-hl-im-color: #00769E;
--quarto-hl-ch-color: #20794D;
--quarto-hl-dt-color: #AD0000;
--quarto-hl-fl-color: #AD0000;
--quarto-hl-co-color: #5E5E5E;
--quarto-hl-cv-color: #5E5E5E;
--quarto-hl-cn-color: #8f5902;
--quarto-hl-sc-color: #5E5E5E;
--quarto-hl-dv-color: #AD0000;
--quarto-hl-kw-color: #003B4F;
}
/* other quarto variables */
:root {
--quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
}
pre > code.sourceCode > span {
color: #003B4F;
}
code span {
color: #003B4F;
}
code.sourceCode > span {
color: #003B4F;
}
div.sourceCode,
div.sourceCode pre.sourceCode {
color: #003B4F;
}
code span.ot {
color: #003B4F;
font-style: inherit;
}
code span.at {
color: #657422;
font-style: inherit;
}
code span.ss {
color: #20794D;
font-style: inherit;
}
code span.an {
color: #5E5E5E;
font-style: inherit;
}
code span.fu {
color: #4758AB;
font-style: inherit;
}
code span.st {
color: #20794D;
font-style: inherit;
}
code span.cf {
color: #003B4F;
font-style: inherit;
}
code span.op {
color: #5E5E5E;
font-style: inherit;
}
code span.er {
color: #AD0000;
font-style: inherit;
}
code span.bn {
color: #AD0000;
font-style: inherit;
}
code span.al {
color: #AD0000;
font-style: inherit;
}
code span.va {
color: #111111;
font-style: inherit;
}
code span.bu {
font-style: inherit;
}
code span.ex {
font-style: inherit;
}
code span.pp {
color: #AD0000;
font-style: inherit;
}
code span.in {
color: #5E5E5E;
font-style: inherit;
}
code span.vs {
color: #20794D;
font-style: inherit;
}
code span.wa {
color: #5E5E5E;
font-style: italic;
}
code span.do {
color: #5E5E5E;
font-style: italic;
}
code span.im {
color: #00769E;
font-style: inherit;
}
code span.ch {
color: #20794D;
font-style: inherit;
}
code span.dt {
color: #AD0000;
font-style: inherit;
}
code span.fl {
color: #AD0000;
font-style: inherit;
}
code span.co {
color: #5E5E5E;
font-style: inherit;
}
code span.cv {
color: #5E5E5E;
font-style: italic;
}
code span.cn {
color: #8f5902;
font-style: inherit;
}
code span.sc {
color: #5E5E5E;
font-style: inherit;
}
code span.dv {
color: #AD0000;
font-style: inherit;
}
code span.kw {
color: #003B4F;
font-style: inherit;
}
.prevent-inlining {
content: "</";
}
/*# sourceMappingURL=debc5d5d77c3f9108843748ff7464032.css.map */

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@@ -0,0 +1,897 @@
const sectionChanged = new CustomEvent("quarto-sectionChanged", {
detail: {},
bubbles: true,
cancelable: false,
composed: false,
});
const layoutMarginEls = () => {
// Find any conflicting margin elements and add margins to the
// top to prevent overlap
const marginChildren = window.document.querySelectorAll(
".column-margin.column-container > * "
);
let lastBottom = 0;
for (const marginChild of marginChildren) {
if (marginChild.offsetParent !== null) {
// clear the top margin so we recompute it
marginChild.style.marginTop = null;
const top = marginChild.getBoundingClientRect().top + window.scrollY;
if (top < lastBottom) {
const margin = lastBottom - top;
marginChild.style.marginTop = `${margin}px`;
}
const styles = window.getComputedStyle(marginChild);
const marginTop = parseFloat(styles["marginTop"]);
lastBottom = top + marginChild.getBoundingClientRect().height + marginTop;
}
}
};
window.document.addEventListener("DOMContentLoaded", function (_event) {
// Recompute the position of margin elements anytime the body size changes
if (window.ResizeObserver) {
const resizeObserver = new window.ResizeObserver(
throttle(() => {
layoutMarginEls();
if (
window.document.body.getBoundingClientRect().width < 990 &&
isReaderMode()
) {
quartoToggleReader();
}
}, 50)
);
resizeObserver.observe(window.document.body);
}
const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]');
const sidebarEl = window.document.getElementById("quarto-sidebar");
const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left");
const marginSidebarEl = window.document.getElementById(
"quarto-margin-sidebar"
);
// function to determine whether the element has a previous sibling that is active
const prevSiblingIsActiveLink = (el) => {
const sibling = el.previousElementSibling;
if (sibling && sibling.tagName === "A") {
return sibling.classList.contains("active");
} else {
return false;
}
};
// fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior)
function fireSlideEnter(e) {
const event = window.document.createEvent("Event");
event.initEvent("slideenter", true, true);
window.document.dispatchEvent(event);
}
const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]');
tabs.forEach((tab) => {
tab.addEventListener("shown.bs.tab", fireSlideEnter);
});
// fire slideEnter for tabby tab activations (for htmlwidget resize behavior)
document.addEventListener("tabby", fireSlideEnter, false);
// Track scrolling and mark TOC links as active
// get table of contents and sidebar (bail if we don't have at least one)
const tocLinks = tocEl
? [...tocEl.querySelectorAll("a[data-scroll-target]")]
: [];
const makeActive = (link) => tocLinks[link].classList.add("active");
const removeActive = (link) => tocLinks[link].classList.remove("active");
const removeAllActive = () =>
[...Array(tocLinks.length).keys()].forEach((link) => removeActive(link));
// activate the anchor for a section associated with this TOC entry
tocLinks.forEach((link) => {
link.addEventListener("click", () => {
if (link.href.indexOf("#") !== -1) {
const anchor = link.href.split("#")[1];
const heading = window.document.querySelector(
`[data-anchor-id=${anchor}]`
);
if (heading) {
// Add the class
heading.classList.add("reveal-anchorjs-link");
// function to show the anchor
const handleMouseout = () => {
heading.classList.remove("reveal-anchorjs-link");
heading.removeEventListener("mouseout", handleMouseout);
};
// add a function to clear the anchor when the user mouses out of it
heading.addEventListener("mouseout", handleMouseout);
}
}
});
});
const sections = tocLinks.map((link) => {
const target = link.getAttribute("data-scroll-target");
if (target.startsWith("#")) {
return window.document.getElementById(decodeURI(`${target.slice(1)}`));
} else {
return window.document.querySelector(decodeURI(`${target}`));
}
});
const sectionMargin = 200;
let currentActive = 0;
// track whether we've initialized state the first time
let init = false;
const updateActiveLink = () => {
// The index from bottom to top (e.g. reversed list)
let sectionIndex = -1;
if (
window.innerHeight + window.pageYOffset >=
window.document.body.offsetHeight
) {
sectionIndex = 0;
} else {
sectionIndex = [...sections].reverse().findIndex((section) => {
if (section) {
return window.pageYOffset >= section.offsetTop - sectionMargin;
} else {
return false;
}
});
}
if (sectionIndex > -1) {
const current = sections.length - sectionIndex - 1;
if (current !== currentActive) {
removeAllActive();
currentActive = current;
makeActive(current);
if (init) {
window.dispatchEvent(sectionChanged);
}
init = true;
}
}
};
const inHiddenRegion = (top, bottom, hiddenRegions) => {
for (const region of hiddenRegions) {
if (top <= region.bottom && bottom >= region.top) {
return true;
}
}
return false;
};
const categorySelector = "header.quarto-title-block .quarto-category";
const activateCategories = (href) => {
// Find any categories
// Surround them with a link pointing back to:
// #category=Authoring
try {
const categoryEls = window.document.querySelectorAll(categorySelector);
for (const categoryEl of categoryEls) {
const categoryText = categoryEl.textContent;
if (categoryText) {
const link = `${href}#category=${encodeURIComponent(categoryText)}`;
const linkEl = window.document.createElement("a");
linkEl.setAttribute("href", link);
for (const child of categoryEl.childNodes) {
linkEl.append(child);
}
categoryEl.appendChild(linkEl);
}
}
} catch {
// Ignore errors
}
};
function hasTitleCategories() {
return window.document.querySelector(categorySelector) !== null;
}
function offsetRelativeUrl(url) {
const offset = getMeta("quarto:offset");
return offset ? offset + url : url;
}
function offsetAbsoluteUrl(url) {
const offset = getMeta("quarto:offset");
const baseUrl = new URL(offset, window.location);
const projRelativeUrl = url.replace(baseUrl, "");
if (projRelativeUrl.startsWith("/")) {
return projRelativeUrl;
} else {
return "/" + projRelativeUrl;
}
}
// read a meta tag value
function getMeta(metaName) {
const metas = window.document.getElementsByTagName("meta");
for (let i = 0; i < metas.length; i++) {
if (metas[i].getAttribute("name") === metaName) {
return metas[i].getAttribute("content");
}
}
return "";
}
async function findAndActivateCategories() {
const currentPagePath = offsetAbsoluteUrl(window.location.href);
const response = await fetch(offsetRelativeUrl("listings.json"));
if (response.status == 200) {
return response.json().then(function (listingPaths) {
const listingHrefs = [];
for (const listingPath of listingPaths) {
const pathWithoutLeadingSlash = listingPath.listing.substring(1);
for (const item of listingPath.items) {
if (
item === currentPagePath ||
item === currentPagePath + "index.html"
) {
// Resolve this path against the offset to be sure
// we already are using the correct path to the listing
// (this adjusts the listing urls to be rooted against
// whatever root the page is actually running against)
const relative = offsetRelativeUrl(pathWithoutLeadingSlash);
const baseUrl = window.location;
const resolvedPath = new URL(relative, baseUrl);
listingHrefs.push(resolvedPath.pathname);
break;
}
}
}
// Look up the tree for a nearby linting and use that if we find one
const nearestListing = findNearestParentListing(
offsetAbsoluteUrl(window.location.pathname),
listingHrefs
);
if (nearestListing) {
activateCategories(nearestListing);
} else {
// See if the referrer is a listing page for this item
const referredRelativePath = offsetAbsoluteUrl(document.referrer);
const referrerListing = listingHrefs.find((listingHref) => {
const isListingReferrer =
listingHref === referredRelativePath ||
listingHref === referredRelativePath + "index.html";
return isListingReferrer;
});
if (referrerListing) {
// Try to use the referrer if possible
activateCategories(referrerListing);
} else if (listingHrefs.length > 0) {
// Otherwise, just fall back to the first listing
activateCategories(listingHrefs[0]);
}
}
});
}
}
if (hasTitleCategories()) {
findAndActivateCategories();
}
const findNearestParentListing = (href, listingHrefs) => {
if (!href || !listingHrefs) {
return undefined;
}
// Look up the tree for a nearby linting and use that if we find one
const relativeParts = href.substring(1).split("/");
while (relativeParts.length > 0) {
const path = relativeParts.join("/");
for (const listingHref of listingHrefs) {
if (listingHref.startsWith(path)) {
return listingHref;
}
}
relativeParts.pop();
}
return undefined;
};
const manageSidebarVisiblity = (el, placeholderDescriptor) => {
let isVisible = true;
let elRect;
return (hiddenRegions) => {
if (el === null) {
return;
}
// Find the last element of the TOC
const lastChildEl = el.lastElementChild;
if (lastChildEl) {
// Converts the sidebar to a menu
const convertToMenu = () => {
for (const child of el.children) {
child.style.opacity = 0;
child.style.overflow = "hidden";
}
nexttick(() => {
const toggleContainer = window.document.createElement("div");
toggleContainer.style.width = "100%";
toggleContainer.classList.add("zindex-over-content");
toggleContainer.classList.add("quarto-sidebar-toggle");
toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom
toggleContainer.id = placeholderDescriptor.id;
toggleContainer.style.position = "fixed";
const toggleIcon = window.document.createElement("i");
toggleIcon.classList.add("quarto-sidebar-toggle-icon");
toggleIcon.classList.add("bi");
toggleIcon.classList.add("bi-caret-down-fill");
const toggleTitle = window.document.createElement("div");
const titleEl = window.document.body.querySelector(
placeholderDescriptor.titleSelector
);
if (titleEl) {
toggleTitle.append(
titleEl.textContent || titleEl.innerText,
toggleIcon
);
}
toggleTitle.classList.add("zindex-over-content");
toggleTitle.classList.add("quarto-sidebar-toggle-title");
toggleContainer.append(toggleTitle);
const toggleContents = window.document.createElement("div");
toggleContents.classList = el.classList;
toggleContents.classList.add("zindex-over-content");
toggleContents.classList.add("quarto-sidebar-toggle-contents");
for (const child of el.children) {
if (child.id === "toc-title") {
continue;
}
const clone = child.cloneNode(true);
clone.style.opacity = 1;
clone.style.display = null;
toggleContents.append(clone);
}
toggleContents.style.height = "0px";
const positionToggle = () => {
// position the element (top left of parent, same width as parent)
if (!elRect) {
elRect = el.getBoundingClientRect();
}
toggleContainer.style.left = `${elRect.left}px`;
toggleContainer.style.top = `${elRect.top}px`;
toggleContainer.style.width = `${elRect.width}px`;
};
positionToggle();
toggleContainer.append(toggleContents);
el.parentElement.prepend(toggleContainer);
// Process clicks
let tocShowing = false;
// Allow the caller to control whether this is dismissed
// when it is clicked (e.g. sidebar navigation supports
// opening and closing the nav tree, so don't dismiss on click)
const clickEl = placeholderDescriptor.dismissOnClick
? toggleContainer
: toggleTitle;
const closeToggle = () => {
if (tocShowing) {
toggleContainer.classList.remove("expanded");
toggleContents.style.height = "0px";
tocShowing = false;
}
};
// Get rid of any expanded toggle if the user scrolls
window.document.addEventListener(
"scroll",
throttle(() => {
closeToggle();
}, 50)
);
// Handle positioning of the toggle
window.addEventListener(
"resize",
throttle(() => {
elRect = undefined;
positionToggle();
}, 50)
);
window.addEventListener("quarto-hrChanged", () => {
elRect = undefined;
});
// Process the click
clickEl.onclick = () => {
if (!tocShowing) {
toggleContainer.classList.add("expanded");
toggleContents.style.height = null;
tocShowing = true;
} else {
closeToggle();
}
};
});
};
// Converts a sidebar from a menu back to a sidebar
const convertToSidebar = () => {
for (const child of el.children) {
child.style.opacity = 1;
child.style.overflow = null;
}
const placeholderEl = window.document.getElementById(
placeholderDescriptor.id
);
if (placeholderEl) {
placeholderEl.remove();
}
el.classList.remove("rollup");
};
if (isReaderMode()) {
convertToMenu();
isVisible = false;
} else {
// Find the top and bottom o the element that is being managed
const elTop = el.offsetTop;
const elBottom =
elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight;
if (!isVisible) {
// If the element is current not visible reveal if there are
// no conflicts with overlay regions
if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
convertToSidebar();
isVisible = true;
}
} else {
// If the element is visible, hide it if it conflicts with overlay regions
// and insert a placeholder toggle (or if we're in reader mode)
if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
convertToMenu();
isVisible = false;
}
}
}
}
};
};
const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]');
for (const tabEl of tabEls) {
const id = tabEl.getAttribute("data-bs-target");
if (id) {
const columnEl = document.querySelector(
`${id} .column-margin, .tabset-margin-content`
);
if (columnEl)
tabEl.addEventListener("shown.bs.tab", function (event) {
const el = event.srcElement;
if (el) {
const visibleCls = `${el.id}-margin-content`;
// walk up until we find a parent tabset
let panelTabsetEl = el.parentElement;
while (panelTabsetEl) {
if (panelTabsetEl.classList.contains("panel-tabset")) {
break;
}
panelTabsetEl = panelTabsetEl.parentElement;
}
if (panelTabsetEl) {
const prevSib = panelTabsetEl.previousElementSibling;
if (
prevSib &&
prevSib.classList.contains("tabset-margin-container")
) {
const childNodes = prevSib.querySelectorAll(
".tabset-margin-content"
);
for (const childEl of childNodes) {
if (childEl.classList.contains(visibleCls)) {
childEl.classList.remove("collapse");
} else {
childEl.classList.add("collapse");
}
}
}
}
}
layoutMarginEls();
});
}
}
// Manage the visibility of the toc and the sidebar
const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, {
id: "quarto-toc-toggle",
titleSelector: "#toc-title",
dismissOnClick: true,
});
const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, {
id: "quarto-sidebarnav-toggle",
titleSelector: ".title",
dismissOnClick: false,
});
let tocLeftScrollVisibility;
if (leftTocEl) {
tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, {
id: "quarto-lefttoc-toggle",
titleSelector: "#toc-title",
dismissOnClick: true,
});
}
// Find the first element that uses formatting in special columns
const conflictingEls = window.document.body.querySelectorAll(
'[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]'
);
// Filter all the possibly conflicting elements into ones
// the do conflict on the left or ride side
const arrConflictingEls = Array.from(conflictingEls);
const leftSideConflictEls = arrConflictingEls.filter((el) => {
if (el.tagName === "ASIDE") {
return false;
}
return Array.from(el.classList).find((className) => {
return (
className !== "column-body" &&
className.startsWith("column-") &&
!className.endsWith("right") &&
!className.endsWith("container") &&
className !== "column-margin"
);
});
});
const rightSideConflictEls = arrConflictingEls.filter((el) => {
if (el.tagName === "ASIDE") {
return true;
}
const hasMarginCaption = Array.from(el.classList).find((className) => {
return className == "margin-caption";
});
if (hasMarginCaption) {
return true;
}
return Array.from(el.classList).find((className) => {
return (
className !== "column-body" &&
!className.endsWith("container") &&
className.startsWith("column-") &&
!className.endsWith("left")
);
});
});
const kOverlapPaddingSize = 10;
function toRegions(els) {
return els.map((el) => {
const boundRect = el.getBoundingClientRect();
const top =
boundRect.top +
document.documentElement.scrollTop -
kOverlapPaddingSize;
return {
top,
bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize,
};
});
}
let hasObserved = false;
const visibleItemObserver = (els) => {
let visibleElements = [...els];
const intersectionObserver = new IntersectionObserver(
(entries, _observer) => {
entries.forEach((entry) => {
if (entry.isIntersecting) {
if (visibleElements.indexOf(entry.target) === -1) {
visibleElements.push(entry.target);
}
} else {
visibleElements = visibleElements.filter((visibleEntry) => {
return visibleEntry !== entry;
});
}
});
if (!hasObserved) {
hideOverlappedSidebars();
}
hasObserved = true;
},
{}
);
els.forEach((el) => {
intersectionObserver.observe(el);
});
return {
getVisibleEntries: () => {
return visibleElements;
},
};
};
const rightElementObserver = visibleItemObserver(rightSideConflictEls);
const leftElementObserver = visibleItemObserver(leftSideConflictEls);
const hideOverlappedSidebars = () => {
marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries()));
sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries()));
if (tocLeftScrollVisibility) {
tocLeftScrollVisibility(
toRegions(leftElementObserver.getVisibleEntries())
);
}
};
window.quartoToggleReader = () => {
// Applies a slow class (or removes it)
// to update the transition speed
const slowTransition = (slow) => {
const manageTransition = (id, slow) => {
const el = document.getElementById(id);
if (el) {
if (slow) {
el.classList.add("slow");
} else {
el.classList.remove("slow");
}
}
};
manageTransition("TOC", slow);
manageTransition("quarto-sidebar", slow);
};
const readerMode = !isReaderMode();
setReaderModeValue(readerMode);
// If we're entering reader mode, slow the transition
if (readerMode) {
slowTransition(readerMode);
}
highlightReaderToggle(readerMode);
hideOverlappedSidebars();
// If we're exiting reader mode, restore the non-slow transition
if (!readerMode) {
slowTransition(!readerMode);
}
};
const highlightReaderToggle = (readerMode) => {
const els = document.querySelectorAll(".quarto-reader-toggle");
if (els) {
els.forEach((el) => {
if (readerMode) {
el.classList.add("reader");
} else {
el.classList.remove("reader");
}
});
}
};
const setReaderModeValue = (val) => {
if (window.location.protocol !== "file:") {
window.localStorage.setItem("quarto-reader-mode", val);
} else {
localReaderMode = val;
}
};
const isReaderMode = () => {
if (window.location.protocol !== "file:") {
return window.localStorage.getItem("quarto-reader-mode") === "true";
} else {
return localReaderMode;
}
};
let localReaderMode = null;
const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded");
const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1;
// Walk the TOC and collapse/expand nodes
// Nodes are expanded if:
// - they are top level
// - they have children that are 'active' links
// - they are directly below an link that is 'active'
const walk = (el, depth) => {
// Tick depth when we enter a UL
if (el.tagName === "UL") {
depth = depth + 1;
}
// It this is active link
let isActiveNode = false;
if (el.tagName === "A" && el.classList.contains("active")) {
isActiveNode = true;
}
// See if there is an active child to this element
let hasActiveChild = false;
for (child of el.children) {
hasActiveChild = walk(child, depth) || hasActiveChild;
}
// Process the collapse state if this is an UL
if (el.tagName === "UL") {
if (tocOpenDepth === -1 && depth > 1) {
el.classList.add("collapse");
} else if (
depth <= tocOpenDepth ||
hasActiveChild ||
prevSiblingIsActiveLink(el)
) {
el.classList.remove("collapse");
} else {
el.classList.add("collapse");
}
// untick depth when we leave a UL
depth = depth - 1;
}
return hasActiveChild || isActiveNode;
};
// walk the TOC and expand / collapse any items that should be shown
if (tocEl) {
walk(tocEl, 0);
updateActiveLink();
}
// Throttle the scroll event and walk peridiocally
window.document.addEventListener(
"scroll",
throttle(() => {
if (tocEl) {
updateActiveLink();
walk(tocEl, 0);
}
if (!isReaderMode()) {
hideOverlappedSidebars();
}
}, 5)
);
window.addEventListener(
"resize",
throttle(() => {
if (!isReaderMode()) {
hideOverlappedSidebars();
}
}, 10)
);
hideOverlappedSidebars();
highlightReaderToggle(isReaderMode());
});
// grouped tabsets
window.addEventListener("pageshow", (_event) => {
function getTabSettings() {
const data = localStorage.getItem("quarto-persistent-tabsets-data");
if (!data) {
localStorage.setItem("quarto-persistent-tabsets-data", "{}");
return {};
}
if (data) {
return JSON.parse(data);
}
}
function setTabSettings(data) {
localStorage.setItem(
"quarto-persistent-tabsets-data",
JSON.stringify(data)
);
}
function setTabState(groupName, groupValue) {
const data = getTabSettings();
data[groupName] = groupValue;
setTabSettings(data);
}
function toggleTab(tab, active) {
const tabPanelId = tab.getAttribute("aria-controls");
const tabPanel = document.getElementById(tabPanelId);
if (active) {
tab.classList.add("active");
tabPanel.classList.add("active");
} else {
tab.classList.remove("active");
tabPanel.classList.remove("active");
}
}
function toggleAll(selectedGroup, selectorsToSync) {
for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) {
const active = selectedGroup === thisGroup;
for (const tab of tabs) {
toggleTab(tab, active);
}
}
}
function findSelectorsToSyncByLanguage() {
const result = {};
const tabs = Array.from(
document.querySelectorAll(`div[data-group] a[id^='tabset-']`)
);
for (const item of tabs) {
const div = item.parentElement.parentElement.parentElement;
const group = div.getAttribute("data-group");
if (!result[group]) {
result[group] = {};
}
const selectorsToSync = result[group];
const value = item.innerHTML;
if (!selectorsToSync[value]) {
selectorsToSync[value] = [];
}
selectorsToSync[value].push(item);
}
return result;
}
function setupSelectorSync() {
const selectorsToSync = findSelectorsToSyncByLanguage();
Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => {
Object.entries(tabSetsByValue).forEach(([value, items]) => {
items.forEach((item) => {
item.addEventListener("click", (_event) => {
setTabState(group, value);
toggleAll(value, selectorsToSync[group]);
});
});
});
});
return selectorsToSync;
}
const selectorsToSync = setupSelectorSync();
for (const [group, selectedName] of Object.entries(getTabSettings())) {
const selectors = selectorsToSync[group];
// it's possible that stale state gives us empty selections, so we explicitly check here.
if (selectors) {
toggleAll(selectedName, selectors);
}
}
});
function throttle(func, wait) {
let waiting = false;
return function () {
if (!waiting) {
func.apply(this, arguments);
waiting = true;
setTimeout(function () {
waiting = false;
}, wait);
}
};
}
function nexttick(func) {
return setTimeout(func, 0);
}

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@@ -0,0 +1 @@
.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center top}.tippy-box[data-placement^=bottom]>.tippy-arrow{top:0}.tippy-box[data-placement^=bottom]>.tippy-arrow:before{top:-7px;left:0;border-width:0 8px 8px;border-bottom-color:initial;transform-origin:center bottom}.tippy-box[data-placement^=left]>.tippy-arrow{right:0}.tippy-box[data-placement^=left]>.tippy-arrow:before{border-width:8px 0 8px 8px;border-left-color:initial;right:-7px;transform-origin:center left}.tippy-box[data-placement^=right]>.tippy-arrow{left:0}.tippy-box[data-placement^=right]>.tippy-arrow:before{left:-7px;border-width:8px 8px 8px 0;border-right-color:initial;transform-origin:center right}.tippy-box[data-inertia][data-state=visible]{transition-timing-function:cubic-bezier(.54,1.5,.38,1.11)}.tippy-arrow{width:16px;height:16px;color:#333}.tippy-arrow:before{content:"";position:absolute;border-color:transparent;border-style:solid}.tippy-content{position:relative;padding:5px 9px;z-index:1}

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const headroomChanged = new CustomEvent("quarto-hrChanged", {
detail: {},
bubbles: true,
cancelable: false,
composed: false,
});
window.document.addEventListener("DOMContentLoaded", function () {
let init = false;
// Manage the back to top button, if one is present.
let lastScrollTop = window.pageYOffset || document.documentElement.scrollTop;
const scrollDownBuffer = 5;
const scrollUpBuffer = 35;
const btn = document.getElementById("quarto-back-to-top");
const hideBackToTop = () => {
btn.style.display = "none";
};
const showBackToTop = () => {
btn.style.display = "inline-block";
};
if (btn) {
window.document.addEventListener(
"scroll",
function () {
const currentScrollTop =
window.pageYOffset || document.documentElement.scrollTop;
// Shows and hides the button 'intelligently' as the user scrolls
if (currentScrollTop - scrollDownBuffer > lastScrollTop) {
hideBackToTop();
lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop;
} else if (currentScrollTop < lastScrollTop - scrollUpBuffer) {
showBackToTop();
lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop;
}
// Show the button at the bottom, hides it at the top
if (currentScrollTop <= 0) {
hideBackToTop();
} else if (
window.innerHeight + currentScrollTop >=
document.body.offsetHeight
) {
showBackToTop();
}
},
false
);
}
function throttle(func, wait) {
var timeout;
return function () {
const context = this;
const args = arguments;
const later = function () {
clearTimeout(timeout);
timeout = null;
func.apply(context, args);
};
if (!timeout) {
timeout = setTimeout(later, wait);
}
};
}
function headerOffset() {
// Set an offset if there is are fixed top navbar
const headerEl = window.document.querySelector("header.fixed-top");
if (headerEl) {
return headerEl.clientHeight;
} else {
return 0;
}
}
function footerOffset() {
const footerEl = window.document.querySelector("footer.footer");
if (footerEl) {
return footerEl.clientHeight;
} else {
return 0;
}
}
function dashboardOffset() {
const dashboardNavEl = window.document.getElementById(
"quarto-dashboard-header"
);
if (dashboardNavEl !== null) {
return dashboardNavEl.clientHeight;
} else {
return 0;
}
}
function updateDocumentOffsetWithoutAnimation() {
updateDocumentOffset(false);
}
function updateDocumentOffset(animated) {
// set body offset
const topOffset = headerOffset();
const bodyOffset = topOffset + footerOffset() + dashboardOffset();
const bodyEl = window.document.body;
bodyEl.setAttribute("data-bs-offset", topOffset);
bodyEl.style.paddingTop = topOffset + "px";
// deal with sidebar offsets
const sidebars = window.document.querySelectorAll(
".sidebar, .headroom-target"
);
sidebars.forEach((sidebar) => {
if (!animated) {
sidebar.classList.add("notransition");
// Remove the no transition class after the animation has time to complete
setTimeout(function () {
sidebar.classList.remove("notransition");
}, 201);
}
if (window.Headroom && sidebar.classList.contains("sidebar-unpinned")) {
sidebar.style.top = "0";
sidebar.style.maxHeight = "100vh";
} else {
sidebar.style.top = topOffset + "px";
sidebar.style.maxHeight = "calc(100vh - " + topOffset + "px)";
sidebar.style.minHeight = "calc(100vh - " + topOffset + "px)";
}
});
// allow space for footer
const mainContainer = window.document.querySelector(".quarto-container");
if (mainContainer) {
mainContainer.style.minHeight = "calc(100vh - " + bodyOffset + "px)";
}
// link offset
let linkStyle = window.document.querySelector("#quarto-target-style");
if (!linkStyle) {
linkStyle = window.document.createElement("style");
linkStyle.setAttribute("id", "quarto-target-style");
window.document.head.appendChild(linkStyle);
}
while (linkStyle.firstChild) {
linkStyle.removeChild(linkStyle.firstChild);
}
if (topOffset > 0) {
linkStyle.appendChild(
window.document.createTextNode(`
section:target::before {
content: "";
display: block;
height: ${topOffset}px;
margin: -${topOffset}px 0 0;
}`)
);
}
if (init) {
window.dispatchEvent(headroomChanged);
}
init = true;
}
// initialize headroom
var header = window.document.querySelector("#quarto-header");
if (header && window.Headroom) {
const headroom = new window.Headroom(header, {
tolerance: 5,
onPin: function () {
const sidebars = window.document.querySelectorAll(
".sidebar, .headroom-target"
);
sidebars.forEach((sidebar) => {
sidebar.classList.remove("sidebar-unpinned");
});
updateDocumentOffset();
},
onUnpin: function () {
const sidebars = window.document.querySelectorAll(
".sidebar, .headroom-target"
);
sidebars.forEach((sidebar) => {
sidebar.classList.add("sidebar-unpinned");
});
updateDocumentOffset();
},
});
headroom.init();
let frozen = false;
window.quartoToggleHeadroom = function () {
if (frozen) {
headroom.unfreeze();
frozen = false;
} else {
headroom.freeze();
frozen = true;
}
};
}
window.addEventListener(
"hashchange",
function (e) {
if (
getComputedStyle(document.documentElement).scrollBehavior !== "smooth"
) {
window.scrollTo(0, window.pageYOffset - headerOffset());
}
},
false
);
// Observe size changed for the header
const headerEl = window.document.querySelector("header.fixed-top");
if (headerEl && window.ResizeObserver) {
const observer = new window.ResizeObserver(() => {
setTimeout(updateDocumentOffsetWithoutAnimation, 0);
});
observer.observe(headerEl, {
attributes: true,
childList: true,
characterData: true,
});
} else {
window.addEventListener(
"resize",
throttle(updateDocumentOffsetWithoutAnimation, 50)
);
}
setTimeout(updateDocumentOffsetWithoutAnimation, 250);
// fixup index.html links if we aren't on the filesystem
if (window.location.protocol !== "file:") {
const links = window.document.querySelectorAll("a");
for (let i = 0; i < links.length; i++) {
if (links[i].href) {
links[i].href = links[i].href.replace(/\/index\.html/, "/");
}
}
// Fixup any sharing links that require urls
// Append url to any sharing urls
const sharingLinks = window.document.querySelectorAll(
"a.sidebar-tools-main-item, a.quarto-navigation-tool, a.quarto-navbar-tools, a.quarto-navbar-tools-item"
);
for (let i = 0; i < sharingLinks.length; i++) {
const sharingLink = sharingLinks[i];
const href = sharingLink.getAttribute("href");
if (href) {
sharingLink.setAttribute(
"href",
href.replace("|url|", window.location.href)
);
}
}
// Scroll the active navigation item into view, if necessary
const navSidebar = window.document.querySelector("nav#quarto-sidebar");
if (navSidebar) {
// Find the active item
const activeItem = navSidebar.querySelector("li.sidebar-item a.active");
if (activeItem) {
// Wait for the scroll height and height to resolve by observing size changes on the
// nav element that is scrollable
const resizeObserver = new ResizeObserver((_entries) => {
// The bottom of the element
const elBottom = activeItem.offsetTop;
const viewBottom = navSidebar.scrollTop + navSidebar.clientHeight;
// The element height and scroll height are the same, then we are still loading
if (viewBottom !== navSidebar.scrollHeight) {
// Determine if the item isn't visible and scroll to it
if (elBottom >= viewBottom) {
navSidebar.scrollTop = elBottom;
}
// stop observing now since we've completed the scroll
resizeObserver.unobserve(navSidebar);
}
});
resizeObserver.observe(navSidebar);
}
}
}
});

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site_libs/quarto-search/fuse.min.js vendored Normal file

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/* css styles */