# axolotl-ai-cloud/axolotl

Go ahead and axolotl questions

Repository: https://github.com/axolotl-ai-cloud/axolotl
Canonical: https://ross.abutalabs.com/products/axolotl
Homepage: https://docs.axolotl.ai
Language: Python
License: Apache-2.0
License Family: permissive
Topics: fine-tuning, llm
Last push: 2026-08-26T14:48:15+00:00

## Health v2 (maintenance only)
Score: 95/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 93, longevity 88
- inputs: {"age_days": 1237, "days_push": 7, "days_rel": 47, "gap_med": 14.0, "n_releases_24m": 27}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 12408, forks 1412 (observed 2026-08-28T04:10:52.629900+00:00)

## What it is
Axolotl is a free, open-source, config-driven framework for fine-tuning large language models, supporting SFT, preference learning (DPO/KTO/ORPO), RL (GRPO), and reward modeling via YAML configs. It supports LoRA, QLoRA, and full fine-tuning across a wide range of HuggingFace model architectures, including multimodal and MoE models, with distributed training via FSDP and DeepSpeed.

## Use cases
- fine-tune an LLM with LoRA on my own instruction dataset
- run QLoRA fine-tuning of a large model on a single GPU
- train a model with DPO using preference pairs
- fine-tune a vision-language model on image-text data
- do GRPO reinforcement learning with a reward function
- merge LoRA adapters into a full model checkpoint
- fine-tune a MoE model with reduced VRAM
- chat interactively with a fine-tuned model for testing

## When to choose
- you want a YAML-config-driven fine-tuning workflow with broad model support
- you need LoRA/QLoRA/full fine-tuning plus SFT, DPO, KTO, ORPO, or GRPO in one tool
- you train on NVIDIA or AMD GPUs, including multi-GPU and cloud setups
- you want cutting-edge features like MoE LoRA, expert parallelism, or BitNet fine-tuning

## When to avoid
- you only need inference or serving of existing models without training
- you have no GPU and cannot use cloud GPU environments
- you need a no-code GUI trainer rather than config files and a CLI
- you train non-LLM models like image classifiers from scratch

## Facets
- artifact type: framework
- maturity: active
- function: llm-training, machine-learning, deep-learning, cli
- domain: large-language-models, machine-learning, deep-learning, artificial-intelligence
- platform: python, cloud
- tags: fine-tuning, lora, qlora, sft, dpo, grpo, huggingface, deepspeed, fsdp, moe, multimodal, yaml-config, linux, docker, gpu

## Member repositories
- axolotl-ai-cloud/axolotl (main) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:52.629900+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:14:06.107017+00:00, confidence not recorded.
  - readme: https://github.com/axolotl-ai-cloud/axolotl (fetched 2026-08-28T04:10:52.629900+00:00, sha b484bba759c9)
  - homepage: https://docs.axolotl.ai (fetched 2026-08-29T08:11:09.246972+00:00, sha 298eb79e89b0)
  - site_page: https://docs.axolotl.ai/docs/getting-started.html (fetched 2026-08-29T08:11:09.250117+00:00, sha 40f6555f4fd7)
  - site_page: https://docs.axolotl.ai/docs/choosing_method.html (fetched 2026-08-29T08:11:09.252246+00:00, sha 7bc10aabb108)
  - site_page: https://docs.axolotl.ai/docs/installation.html (fetched 2026-08-29T08:11:09.254453+00:00, sha 8c6824fd5728)
  - site_page: https://docs.axolotl.ai/docs/inference.html (fetched 2026-08-29T08:11:09.256241+00:00, sha 4d7752a18205)
  - site_page: https://docs.axolotl.ai/docs/support-matrix.html (fetched 2026-08-29T08:11:09.258235+00:00, sha 5b99a2388789)
  - site_page: https://docs.axolotl.ai/docs/models/muse-glimmer.html (fetched 2026-08-29T08:11:09.260405+00:00, sha 92b8e802ba35)
  - site_page: https://docs.axolotl.ai/docs/models/cohere-north-micro-vision-instruct.html (fetched 2026-08-29T08:11:09.262147+00:00, sha 23e005159de7)
  - site_page: https://docs.axolotl.ai/docs/models/shieldstral.html (fetched 2026-08-29T08:11:09.263739+00:00, sha 340de848ca36)
- Data as of 2026-08-30T08:39:29.467469+00:00.