Peft projects on GitHub

Parameter-efficient fine-tuning methods like LoRA for large models.

As of October 17, 2026, the most-starred Peft projects on GitHub are LlamaFactory (75.5K stars), happy-llm (34.4K stars) and llm-action (25.2K stars). GitHub.Locker tracks 8 Peft repositories with 193.8K stars combined. The fastest-growing on October 16 was Soup, with +79 stars in a day.

8Projects

193.8KStars in total

+137Stars in a day

Browse in the catalog →github.com/topics/peft ↗

Hot right now

Most stars gained in a day · Oct 16

+79

Soup

MakazhanAlpamys/Soup · ★ 9.2K

Soup is a command-line tool for fine-tuning and post-training LLMs from a single YAML config file, automating GPU detection, batching and quantization so you just write a config and run one command.

+24

LlamaFactory

hiyouga/LlamaFactory · ★ 75.5K

LlamaFactory unifies efficient fine-tuning of 100+ large language models and vision-language models in one Python toolkit, published as an ACL 2024 paper.

+18

happy-llm

datawhalechina/happy-llm · ★ 34.4K

Happy-LLM is Datawhale's free open-source LLM course: a systematic tutorial that goes from NLP basics and the Transformer architecture to building and training your first large language model, then applying it with RAG and agents.

peft

huggingface/peft · ★ 21.8K

Hugging Face's library of Parameter-Efficient Fine-Tuning methods: you adapt a large pretrained model by training only a small number of extra parameters instead of all of them, which slashes compute and storage costs.

The all-time top

8 projects · by stars

#1 · hiyouga/LlamaFactory
LlamaFactory
LlamaFactory unifies efficient fine-tuning of 100+ large language models and vision-language models in one Python toolkit, published as an ACL 2024 paper.
75.5K
#2 · datawhalechina/happy-llm
happy-llm
Happy-LLM is Datawhale's free open-source LLM course: a systematic tutorial that goes from NLP basics and the Transformer architecture to building and training your first large language model, then applying it with RAG and agents.
34.4K
#3 · liguodongiot/llm-action
llm-action
It is a Chinese-language hub of in-depth tutorials on large language model engineering: training, fine-tuning, distributed training, inference, compression, evaluation, data engineering, LLMOps and AI infrastructure, organized as a big index linking the author's article series, many with companion code.
25.2K

4
peft
21.8Khuggingface/peft · Python
Hugging Face's library of Parameter-Efficient Fine-Tuning methods: you adapt a large pretrained model by training only a small number of extra parameters instead of all of them, which slashes compute and storage costs.
5
ms-swift
15.9Kmodelscope/ms-swift · Python
ms-swift is the ModelScope community's fine-tuning and deployment framework for LLMs and multimodal models, covering training, inference, evaluation, quantization and deployment in one pipeline.
6
qlora
11Kartidoro/qlora · Jupyter Notebook
QLoRA is a research method and code release for efficiently finetuning large quantized language models. It backpropagates gradients through a frozen 4-bit quantized model into small LoRA adapters, cutting memory use enough to finetune a 65B model on a single 48GB GPU while matching full 16-bit finetuning quality.
7
Soup
9.2KMakazhanAlpamys/Soup · Python
Soup is a command-line tool for fine-tuning and post-training LLMs from a single YAML config file, automating GPU detection, batching and quantization so you just write a config and run one command.
8
halo
825whitecircle/halo · Python
Halo is an open-source framework from White Circle for training large language and multimodal models: pre-training, SFT, preference optimization, and fully asynchronous multi-turn RL in one codebase, from a single GPU up to multi-node clusters.