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hiyouga / LlamaFactory

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

Why this job: says: fine tuning; topics: fine-tuning, lora, rlhf, peft

What it does

  • Various models. LLaMA, LLaVA, Mistral, Mixtral-MoE, Qwen3, Qwen3-VL, DeepSeek, Gemma, GLM, Phi, etc.
  • Integrated methods. (Continuous) pre-training, (multimodal) supervised fine-tuning, reward modeling, PPO, DPO, KTO, ORPO, etc.
  • Scalable resources. 16-bit full-tuning, freeze-tuning, LoRA and 2/3/4/5/6/8-bit QLoRA via AQLM/AWQ/GPTQ/LLM.int8/HQQ/EETQ.
  • Advanced algorithms. GaLore, BAdam, APOLLO, Adam-mini, Muon, OFT, DoRA, LongLoRA, LLaMA Pro, Mixture-of-Depths, LoRA+, LoftQ and PiSSA.
  • Practical tricks. FlashAttention-2, Unsloth, Liger Kernel, KTransformers, RoPE scaling, NEFTune and rsLoRA.

Get started

docker run -it --rm --gpus=all --ipc=host hiyouga/llamafactory:latest
Maintenance
Active
Last commit today
Stars
75,952
+116 this week
Licence
Apache-2.0
Allows business use
Downloads for
None listed
No release files
Latest version
v0.9.5
Released 5 months ago
Built with
Python
100% of the code

Is it looked after?

Contributors
19
Last 90 days
Issues
87% closed
1,016 still open
Pull requests
1,049 merged
205 waiting
Releases
36
2 in the last year

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More: languages, topics and project record

Languages

  • Python 100%
  • Dockerfile <1%
  • Makefile <1%

Topics

  • fine-tuning
  • llama
  • llm
  • peft
  • transformers
  • rlhf
  • qlora
  • quantization
  • qwen
  • instruction-tuning
  • gpt
  • lora

Project record

  • JobFine-tuning
  • StatusFeatured
  • Commits3,119
  • Forks9,354
  • Watching343
  • Stars in 28 days+623
  • CreatedMay 28, 2023
  • First seen by usNov 7, 2026
  • CheckedNov 9, 2026

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