LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
Authors: name: Yaowei Zheng, name: Richong Zhang, name: Junhao Zhang, name: Yanhan Ye, name: Zheyan Luo

Efficient fine-tuning is vital for adapting large language models (LLMs) to
downstream tasks. However, it requires non-trivial efforts to implement these
methods on different models. We present LlamaFactory, a unified framework that
integrates a suite of cutting-edge efficient training methods. It allows users
to flexibly customize the fine-tuning of 100+ LLMs without the need for coding
through the built-in web UI LlamaBoard. We empirically validate the efficiency
and effectiveness of our framework on language modeling and text generation
tasks. It has been released at https://github.com/hiyouga/LLaMA-Factory and
already received over 13,000 stars and 1,600 forks.