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2025-01-29 04:24:41 +00:00
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commit e67e4191d1
6 changed files with 38 additions and 58 deletions
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22
.github/workflows/main.yml vendored
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@@ -15,16 +15,6 @@ jobs:
fail-fast: false
matrix:
include:
- cuda: 121
cuda_version: 12.1.1
python_version: "3.10"
pytorch: 2.3.1
axolotl_extras: mamba-ssm
- cuda: 121
cuda_version: 12.1.1
python_version: "3.11"
pytorch: 2.3.1
axolotl_extras: mamba-ssm
- cuda: 124
cuda_version: 12.4.1
python_version: "3.11"
@@ -82,16 +72,6 @@ jobs:
strategy:
matrix:
include:
- cuda: 121
cuda_version: 12.1.1
python_version: "3.10"
pytorch: 2.3.1
axolotl_extras:
- cuda: 121
cuda_version: 12.1.1
python_version: "3.11"
pytorch: 2.3.1
axolotl_extras:
- cuda: 124
cuda_version: 12.4.1
python_version: "3.11"
@@ -148,7 +128,7 @@ jobs:
- cuda: 121
cuda_version: 12.1.1
python_version: "3.11"
pytorch: 2.3.1
pytorch: 2.4.1
axolotl_extras:
runs-on: axolotl-gpu-runner
steps:

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.nojekyll
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@@ -1 +1 @@
907d35b7
ed280e0b

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docs/dataset-formats/index.html
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@@ -363,7 +363,7 @@ Description
</tr>
</thead>
<tbody class="list">
<tr data-index="0" data-listing-file-modified-sort="1737741398671" data-listing-reading-time-sort="1" data-listing-word-count-sort="92" data-listing-title-sort="Pre-training" data-listing-filename-sort="pretraining.qmd">
<tr data-index="0" data-listing-file-modified-sort="1738124636858" data-listing-reading-time-sort="1" data-listing-word-count-sort="92" data-listing-title-sort="Pre-training" data-listing-filename-sort="pretraining.qmd">
<td>
<a href="../../docs/dataset-formats/pretraining.html" class="title listing-title">Pre-training</a>
</td>
@@ -371,7 +371,7 @@ Description
<span class="listing-description">Data format for a pre-training completion task.</span>
</td>
</tr>
<tr data-index="1" data-listing-file-modified-sort="1737741398671" data-listing-reading-time-sort="2" data-listing-word-count-sort="308" data-listing-title-sort="Instruction Tuning" data-listing-filename-sort="inst_tune.qmd">
<tr data-index="1" data-listing-file-modified-sort="1738124636858" data-listing-reading-time-sort="2" data-listing-word-count-sort="308" data-listing-title-sort="Instruction Tuning" data-listing-filename-sort="inst_tune.qmd">
<td>
<a href="../../docs/dataset-formats/inst_tune.html" class="title listing-title">Instruction Tuning</a>
</td>
@@ -379,7 +379,7 @@ Description
<span class="listing-description">Instruction tuning formats for supervised fine-tuning.</span>
</td>
</tr>
<tr data-index="2" data-listing-file-modified-sort="1737741398671" data-listing-reading-time-sort="4" data-listing-word-count-sort="625" data-listing-title-sort="Conversation" data-listing-filename-sort="conversation.qmd">
<tr data-index="2" data-listing-file-modified-sort="1738124636858" data-listing-reading-time-sort="4" data-listing-word-count-sort="625" data-listing-title-sort="Conversation" data-listing-filename-sort="conversation.qmd">
<td>
<a href="../../docs/dataset-formats/conversation.html" class="title listing-title">Conversation</a>
</td>
@@ -387,7 +387,7 @@ Description
<span class="listing-description">Conversation format for supervised fine-tuning.</span>
</td>
</tr>
<tr data-index="3" data-listing-file-modified-sort="1737741398671" data-listing-reading-time-sort="1" data-listing-word-count-sort="3" data-listing-title-sort="Template-Free" data-listing-filename-sort="template_free.qmd">
<tr data-index="3" data-listing-file-modified-sort="1738124636858" data-listing-reading-time-sort="1" data-listing-word-count-sort="3" data-listing-title-sort="Template-Free" data-listing-filename-sort="template_free.qmd">
<td>
<a href="../../docs/dataset-formats/template_free.html" class="title listing-title">Template-Free</a>
</td>
@@ -395,7 +395,7 @@ Description
<span class="listing-description">Construct prompts without a template.</span>
</td>
</tr>
<tr data-index="4" data-listing-file-modified-sort="1737741398671" data-listing-reading-time-sort="1" data-listing-word-count-sort="92" data-listing-title-sort="Custom Pre-Tokenized Dataset" data-listing-filename-sort="tokenized.qmd">
<tr data-index="4" data-listing-file-modified-sort="1738124636858" data-listing-reading-time-sort="1" data-listing-word-count-sort="92" data-listing-title-sort="Custom Pre-Tokenized Dataset" data-listing-filename-sort="tokenized.qmd">
<td>
<a href="../../docs/dataset-formats/tokenized.html" class="title listing-title">Custom Pre-Tokenized Dataset</a>
</td>

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index.html
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@@ -368,7 +368,7 @@ pre > code.sourceCode > span > a:first-child::before { text-decoration: underlin
<section id="quickstart" class="level2">
<h2 class="anchored" data-anchor-id="quickstart">Quickstart ⚡</h2>
<p>Get started with Axolotl in just a few steps! This quickstart guide will walk you through setting up and running a basic fine-tuning task.</p>
<p><strong>Requirements</strong>: <em>Nvidia</em> GPU (Ampere architecture or newer for <code>bf16</code> and Flash Attention) or <em>AMD</em> GPU, Python &gt;=3.10 and PyTorch &gt;=2.3.1.</p>
<p><strong>Requirements</strong>: <em>Nvidia</em> GPU (Ampere architecture or newer for <code>bf16</code> and Flash Attention) or <em>AMD</em> GPU, Python &gt;=3.10 and PyTorch &gt;=2.4.1.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="ex">pip3</span> install <span class="at">--no-build-isolation</span> axolotl<span class="pp">[</span><span class="ss">flash</span><span class="pp">-</span><span class="ss">attn,deepspeed</span><span class="pp">]</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="co"># download examples and optionally deepspeed configs to the local path</span></span>

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search.json
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@@ -557,7 +557,7 @@
"href": "index.html#quickstart",
"title": "Axolotl",
"section": "Quickstart ⚡",
"text": "Quickstart ⚡\nGet started with Axolotl in just a few steps! This quickstart guide will walk you through setting up and running a basic fine-tuning task.\nRequirements: Nvidia GPU (Ampere architecture or newer for bf16 and Flash Attention) or AMD GPU, Python &gt;=3.10 and PyTorch &gt;=2.3.1.\npip3 install --no-build-isolation axolotl[flash-attn,deepspeed]\n\n# download examples and optionally deepspeed configs to the local path\naxolotl fetch examples\naxolotl fetch deepspeed_configs # OPTIONAL\n\n# finetune using lora\naxolotl train examples/llama-3/lora-1b.yml\n\nEdge Builds 🏎️\nIf you’re looking for the latest features and updates between releases, you’ll need to install from source.\ngit clone https://github.com/axolotl-ai-cloud/axolotl.git\ncd axolotl\npip3 install packaging ninja\npip3 install --no-build-isolation -e '.[flash-attn,deepspeed]'\n\n\nAxolotl CLI Usage\nWe now support a new, more streamlined CLI using click.\n# preprocess datasets - optional but recommended\nCUDA_VISIBLE_DEVICES=\"0\" axolotl preprocess examples/llama-3/lora-1b.yml\n\n# finetune lora\naxolotl train examples/llama-3/lora-1b.yml\n\n# inference\naxolotl inference examples/llama-3/lora-1b.yml \\\n --lora-model-dir=\"./outputs/lora-out\"\n\n# gradio\naxolotl inference examples/llama-3/lora-1b.yml \\\n --lora-model-dir=\"./outputs/lora-out\" --gradio\n\n# remote yaml files - the yaml config can be hosted on a public URL\n# Note: the yaml config must directly link to the **raw** yaml\naxolotl train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/llama-3/lora-1b.yml\nWe’ve also added a new command for fetching examples and deepspeed_configs to your local machine. This will come in handy when installing axolotl from PyPI.\n# Fetch example YAML files (stores in \"examples/\" folder)\naxolotl fetch examples\n\n# Fetch deepspeed config files (stores in \"deepspeed_configs/\" folder)\naxolotl fetch deepspeed_configs\n\n# Optionally, specify a destination folder\naxolotl fetch examples --dest path/to/folder\n\n\nLegacy Usage\n\n\nClick to Expand\n\nWhile the Axolotl CLI is the preferred method for interacting with axolotl, we still support the legacy -m axolotl.cli.* usage.\n# preprocess datasets - optional but recommended\nCUDA_VISIBLE_DEVICES=\"0\" python -m axolotl.cli.preprocess examples/llama-3/lora-1b.yml\n\n# finetune lora\naccelerate launch -m axolotl.cli.train examples/llama-3/lora-1b.yml\n\n# inference\naccelerate launch -m axolotl.cli.inference examples/llama-3/lora-1b.yml \\\n --lora_model_dir=\"./outputs/lora-out\"\n\n# gradio\naccelerate launch -m axolotl.cli.inference examples/llama-3/lora-1b.yml \\\n --lora_model_dir=\"./outputs/lora-out\" --gradio\n\n# remote yaml files - the yaml config can be hosted on a public URL\n# Note: the yaml config must directly link to the **raw** yaml\naccelerate launch -m axolotl.cli.train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/llama-3/lora-1b.yml",
"text": "Quickstart ⚡\nGet started with Axolotl in just a few steps! This quickstart guide will walk you through setting up and running a basic fine-tuning task.\nRequirements: Nvidia GPU (Ampere architecture or newer for bf16 and Flash Attention) or AMD GPU, Python &gt;=3.10 and PyTorch &gt;=2.4.1.\npip3 install --no-build-isolation axolotl[flash-attn,deepspeed]\n\n# download examples and optionally deepspeed configs to the local path\naxolotl fetch examples\naxolotl fetch deepspeed_configs # OPTIONAL\n\n# finetune using lora\naxolotl train examples/llama-3/lora-1b.yml\n\nEdge Builds 🏎️\nIf you’re looking for the latest features and updates between releases, you’ll need to install from source.\ngit clone https://github.com/axolotl-ai-cloud/axolotl.git\ncd axolotl\npip3 install packaging ninja\npip3 install --no-build-isolation -e '.[flash-attn,deepspeed]'\n\n\nAxolotl CLI Usage\nWe now support a new, more streamlined CLI using click.\n# preprocess datasets - optional but recommended\nCUDA_VISIBLE_DEVICES=\"0\" axolotl preprocess examples/llama-3/lora-1b.yml\n\n# finetune lora\naxolotl train examples/llama-3/lora-1b.yml\n\n# inference\naxolotl inference examples/llama-3/lora-1b.yml \\\n --lora-model-dir=\"./outputs/lora-out\"\n\n# gradio\naxolotl inference examples/llama-3/lora-1b.yml \\\n --lora-model-dir=\"./outputs/lora-out\" --gradio\n\n# remote yaml files - the yaml config can be hosted on a public URL\n# Note: the yaml config must directly link to the **raw** yaml\naxolotl train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/llama-3/lora-1b.yml\nWe’ve also added a new command for fetching examples and deepspeed_configs to your local machine. This will come in handy when installing axolotl from PyPI.\n# Fetch example YAML files (stores in \"examples/\" folder)\naxolotl fetch examples\n\n# Fetch deepspeed config files (stores in \"deepspeed_configs/\" folder)\naxolotl fetch deepspeed_configs\n\n# Optionally, specify a destination folder\naxolotl fetch examples --dest path/to/folder\n\n\nLegacy Usage\n\n\nClick to Expand\n\nWhile the Axolotl CLI is the preferred method for interacting with axolotl, we still support the legacy -m axolotl.cli.* usage.\n# preprocess datasets - optional but recommended\nCUDA_VISIBLE_DEVICES=\"0\" python -m axolotl.cli.preprocess examples/llama-3/lora-1b.yml\n\n# finetune lora\naccelerate launch -m axolotl.cli.train examples/llama-3/lora-1b.yml\n\n# inference\naccelerate launch -m axolotl.cli.inference examples/llama-3/lora-1b.yml \\\n --lora_model_dir=\"./outputs/lora-out\"\n\n# gradio\naccelerate launch -m axolotl.cli.inference examples/llama-3/lora-1b.yml \\\n --lora_model_dir=\"./outputs/lora-out\" --gradio\n\n# remote yaml files - the yaml config can be hosted on a public URL\n# Note: the yaml config must directly link to the **raw** yaml\naccelerate launch -m axolotl.cli.train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/llama-3/lora-1b.yml",
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