From 347001237a8ff845fc23f678107fc505361f9f13 Mon Sep 17 00:00:00 2001 From: Alan Ji Date: Thu, 10 Aug 2023 23:13:39 +0800 Subject: [PATCH] docs: add LLaMA-Efficient-Tuning to awesome-transformers (#25441) Co-authored-by: statelesshz --- awesome-transformers.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/awesome-transformers.md b/awesome-transformers.md index dad4da8a84..013f88259c 100644 --- a/awesome-transformers.md +++ b/awesome-transformers.md @@ -601,3 +601,9 @@ All Hugging Face models and pipelines can be seamlessly integrated into BentoML Keywords: BentoML, Framework, Deployment, AI Applications +## [LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning) + +[LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning) offers a user-friendly fine-tuning framework that incorporates PEFT. The repository includes training(fine-tuning) and inference examples for LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, and other LLMs. A ChatGLM version is also available in [ChatGLM-Efficient-Tuning](https://github.com/hiyouga/ChatGLM-Efficient-Tuning). + +Keywords: PEFT, fine-tuning, LLaMA-2, ChatGLM, Qwen +