Topics / #qlora

Qlora projects on GitHub

Quantized low-rank fine-tuning method for large language models.

As of October 17, 2026, the most-starred Qlora projects on GitHub are unsloth (78.2K stars), LlamaFactory (75.5K stars) and airllm (39.1K stars). GitHub.Locker tracks 9 Qlora repositories with 262.1K stars combined. The fastest-growing on October 16 was airllm, with +159 stars in a day.

9Projects

262.1KStars in total

+340Stars in a day

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

Hot right now

Most stars gained in a day · Oct 16

+159

airllm

lyogavin/airllm · ★ 39.1K

An open-source Python library that runs huge LLMs on tiny GPUs: a 70B model fits on a single 4GB card without quantization, distillation or pruning — even the 2.8T-parameter Kimi K3 runs in under 4GB.

+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.

+56

unsloth

unslothai/unsloth · ★ 78.2K

Unsloth is a local-first app for running and training LLMs, diffusion, TTS and embedding models on your own machine, including models like Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4 and FLUX.

+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.

The all-time top

9 projects · by stars

#1 · unslothai/unsloth
unsloth
Unsloth is a local-first app for running and training LLMs, diffusion, TTS and embedding models on your own machine, including models like Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4 and FLUX.
78.2K
#2 · 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
#3 · lyogavin/airllm
airllm
An open-source Python library that runs huge LLMs on tiny GPUs: a 70B model fits on a single 4GB card without quantization, distillation or pruning — even the 2.8T-parameter Kimi K3 runs in under 4GB.
39.1K

4
happy-llm
34.4Kdatawhalechina/happy-llm · Jupyter Notebook
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.
5
litgpt
13.7KLightning-AI/litgpt · Python
LitGPT is a collection of 20+ high-performance large language models (Llama, Gemma, Phi, Qwen, Mistral, Falcon, TinyLlama and more) implemented from scratch, with ready-made recipes to pretrain, finetune, evaluate and deploy them at scale.
- tpu
- llama
- llms
- lora
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.
9
swarm-agent
190lyt2003-yt/swarm-agent · Python
SwarmAgent is a conversational agent that turns natural-language requests like 'choreograph this song, make the second section gentler' into validated drone-swarm trajectories, built on the ReAct paradigm and sitting on top of a separately deployed SwarmGPT service.