{"schema":"record/v1","id":"src_01M6VCWY17MKFWRGH2PJETKQZM","type":"source","revision":1,"etag":"\"r1.s0\"","title":"Axolotl: LLM fine-tuning toolkit, README overview","summary":"The README presents Axolotl as a toolkit for fine-tuning LLMs from config files.","status":"active","body":{"text":"What it supplies: The README presents Axolotl as a toolkit for fine-tuning LLMs from config files.\n\nUseful for: - Fine-tune models with LoRA or QLoRA and DeepSpeed.\n- Export results to GGUF for llama.cpp or Ollama.\n\nFirst action: - Create a Python 3.12 virtual environment with uv and install torch.\n- Install axolotl[deepspeed] and run axolotl fetch examples.\n\nPrerequisites and limits: An NVIDIA GPU (Ampere or newer for bf16 and Flash Attention) or AMD GPU, Python 3.12 or later and a recent PyTorch per the README.\n\n- It needs a capable GPU.\n- Model-specific configs are in docs that were not read.\n\nSource-documented: Apache 2.0. Base models and datasets carry their own licences.\n\nWritten from the README text only. Statements are as the README gives them; nothing was installed or run.\nBased on updates, quick start, installation and licence README text only; other sections were not read. Nothing was installed or run.\n\nSource inspected: https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/620c1efca4470c1bc2e4a5f46b4b106341e9dc41/README.md ; 21710 bytes ; sha256 159d380744a976ba8dd0e9d02d331f2ef6b79ff78132f1fa89ca526de59a56f8 ; 6 exact pinned excerpts in the draft pin map","archived":null,"revision":{"ref":"commit 620c1efca4470c1bc2e4a5f46b4b106341e9dc41","pinned":false,"source_url":"https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/620c1efca4470c1bc2e4a5f46b4b106341e9dc41/README.md"},"checked_at":"2026-11-07T11:56:59.318Z","parent_url":null,"usefulness":"- Fine-tune models with LoRA or QLoRA and DeepSpeed.\n- Export results to GGUF for llama.cpp or Ollama.","source_type":"repository","availability":"available","dependencies":[],"source_owner":"Axolotl AI (declared repository namespace)","canonical_url":"https://github.com/axolotl-ai-cloud/axolotl","next_check_at":null,"successor_url":null,"hardware_notes":null,"known_limitations":["An NVIDIA GPU (Ampere or newer for bf16 and Flash Attention) or AMD GPU, Python 3.12 or later and a recent PyTorch per the README.\n\n- It needs a capable GPU.\n- Model-specific configs are in docs that were not read.\n\nSource-documented: Apache 2.0. 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Base models and datasets carry their own licences.\n\nWritten from the README text only. Statements are as the README gives them; nothing was installed or run.\nBased on updates, quick start, installation and licence README text only; other sections were not read. Nothing was installed or run.\n\nSource inspected: https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/620c1efca4470c1bc2e4a5f46b4b106341e9dc41/README.md ; 21710 bytes ; sha256 159d380744a976ba8dd0e9d02d331f2ef6b79ff78132f1fa89ca526de59a56f8 ; 6 exact pinned excerpts in the draft pin map","revision":{"ref":"commit 620c1efca4470c1bc2e4a5f46b4b106341e9dc41","pinned":false,"source_url":"https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/620c1efca4470c1bc2e4a5f46b4b106341e9dc41/README.md"},"checked_at":"2026-11-07T11:56:59.318Z","usefulness":"- Fine-tune models with LoRA or QLoRA and DeepSpeed.\n- Export results to GGUF for llama.cpp or Ollama.","source_type":"repository","availability":"available","source_owner":"Axolotl AI (declared repository namespace)","canonical_url":"https://github.com/axolotl-ai-cloud/axolotl","known_limitations":["An NVIDIA GPU (Ampere or newer for bf16 and Flash Attention) or AMD GPU, Python 3.12 or later and a recent PyTorch per the README.\n\n- It needs a capable GPU.\n- Model-specific configs are in docs that were not read.\n\nSource-documented: Apache 2.0. 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