diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 89b2746e4..4f8074ad1 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -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: diff --git a/.nojekyll b/.nojekyll index 446ec107d..afc349f6e 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -907d35b7 \ No newline at end of file +ed280e0b \ No newline at end of file diff --git a/docs/dataset-formats/index.html b/docs/dataset-formats/index.html index cad6a42eb..c6781595a 100644 --- a/docs/dataset-formats/index.html +++ b/docs/dataset-formats/index.html @@ -363,7 +363,7 @@ Description - + Pre-training @@ -371,7 +371,7 @@ Description Data format for a pre-training completion task. - + Instruction Tuning @@ -379,7 +379,7 @@ Description Instruction tuning formats for supervised fine-tuning. - + Conversation @@ -387,7 +387,7 @@ Description Conversation format for supervised fine-tuning. - + Template-Free @@ -395,7 +395,7 @@ Description Construct prompts without a template. - + Custom Pre-Tokenized Dataset diff --git a/index.html b/index.html index 07c175538..ea8534b49 100644 --- a/index.html +++ b/index.html @@ -368,7 +368,7 @@ pre > code.sourceCode > span > a:first-child::before { text-decoration: underlin

Quickstart ⚡

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.

-

Requirements: Nvidia GPU (Ampere architecture or newer for bf16 and Flash Attention) or AMD GPU, Python >=3.10 and PyTorch >=2.3.1.

+

Requirements: Nvidia GPU (Ampere architecture or newer for bf16 and Flash Attention) or AMD GPU, Python >=3.10 and PyTorch >=2.4.1.

pip3 install --no-build-isolation axolotl[flash-attn,deepspeed]
 
 # download examples and optionally deepspeed configs to the local path
diff --git a/search.json b/search.json
index 25c7d5b13..13ce20ad9 100644
--- a/search.json
+++ b/search.json
@@ -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 >=3.10 and PyTorch >=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 >=3.10 and PyTorch >=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",
     "crumbs": [
       "Home"
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diff --git a/sitemap.xml b/sitemap.xml
index 8e4eaa97b..aaa4c2db4 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -2,118 +2,118 @@
 
   
     https://axolotl-ai-cloud.github.io/axolotl/FAQS.html
-    2025-01-24T17:56:38.669Z
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     https://axolotl-ai-cloud.github.io/axolotl/docs/dataset-formats/inst_tune.html
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