From a4310969e837255edc63b81588cdded56b8e9951 Mon Sep 17 00:00:00 2001 From: Quarto GHA Workflow Runner Date: Thu, 22 Aug 2024 17:11:47 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- docs/dataset-formats/index.html | 10 +++---- index.html | 1 + sitemap.xml | 48 ++++++++++++++++----------------- 4 files changed, 31 insertions(+), 30 deletions(-) diff --git a/.nojekyll b/.nojekyll index c02634b4c..c8b597ace 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -9f29351e \ No newline at end of file +2247c440 \ No newline at end of file diff --git a/docs/dataset-formats/index.html b/docs/dataset-formats/index.html index 3b2213b2b..9f629d201 100644 --- a/docs/dataset-formats/index.html +++ b/docs/dataset-formats/index.html @@ -357,7 +357,7 @@ Description - + Pre-training @@ -365,7 +365,7 @@ Description Data format for a pre-training completion task. - + Instruction Tuning @@ -373,7 +373,7 @@ Description Instruction tuning formats for supervised fine-tuning. - + Conversation @@ -381,7 +381,7 @@ Description Conversation format for supervised fine-tuning. - + Template-Free @@ -389,7 +389,7 @@ Description Construct prompts without a template. - + Custom Pre-Tokenized Dataset diff --git a/index.html b/index.html index f52f407c6..2afac44de 100644 --- a/index.html +++ b/index.html @@ -356,6 +356,7 @@ pre > code.sourceCode > span > a:first-child::before { text-decoration: underlin

Axolotl

+

tests multigpu-semi-weekly tests

Axolotl is a tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures.

Features: - Train various Huggingface models such as llama, pythia, falcon, mpt - Supports fullfinetune, lora, qlora, relora, and gptq - Customize configurations using a simple yaml file or CLI overwrite - Load different dataset formats, use custom formats, or bring your own tokenized datasets - Integrated with xformer, flash attention, rope scaling, and multipacking - Works with single GPU or multiple GPUs via FSDP or Deepspeed - Easily run with Docker locally or on the cloud - Log results and optionally checkpoints to wandb or mlflow - And more!

phorm.ai

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