riaz.somc/transformers
1
0
Fork 0
mirror of https://github.com/huggingface/transformers.git synced 2025-07-03 21:00:08 +06:00
Code Issues Actions 25 Packages Projects Releases Wiki Activity

docs: add LLaMA-Efficient-Tuning to awesome-transformers (#25441)

Browse Source 
Co-authored-by: statelesshz <jihuazhong1@huawei.com>
This commit is contained in:
Alan Ji 2023-08-10 23:13:39 +08:00 committed by GitHub
parent a7da2996a0
commit 347001237a
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 6 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
awesome-transformers.md
View File

@ -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