“LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models”, Yaowei Zheng, Richong Zhang, Junhao Zhang, Yanhan Ye, Zheyan Luo, Yongqiang Ma2024-03-20 (reduced-precision NNs)⁠:

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 GitHub and already received over 13,000 stars and 1,600 forks.