From 3dd50cd7f9c36f359da51c563daf0bc465ee4e46 Mon Sep 17 00:00:00 2001 From: Klaus Hipp Date: Tue, 6 Feb 2024 04:06:29 +0100 Subject: [PATCH] [Docs] Update project names and links in awesome-transformers (#28878) Update project names and repository links in awesome-transformers --- awesome-transformers.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/awesome-transformers.md b/awesome-transformers.md index 013f88259c91e4..2ecdd3406f7095 100644 --- a/awesome-transformers.md +++ b/awesome-transformers.md @@ -21,7 +21,7 @@ This repository contains examples and best practices for building recommendation Keywords: Recommender systems, AzureML -## [lama-cleaner](https://github.com/Sanster/lama-cleaner) +## [IOPaint](https://github.com/Sanster/IOPaint) Image inpainting tool powered by Stable Diffusion. Remove any unwanted object, defect, people from your pictures or erase and replace anything on your pictures. @@ -105,9 +105,9 @@ An open-source Implementation of Imagen, Google's closed-source Text-to-Image Ne Keywords: Imagen, Text-to-image -## [adapter-transformers](https://github.com/adapter-hub/adapter-transformers) +## [adapters](https://github.com/adapter-hub/adapters) -[adapter-transformers](https://github.com/adapter-hub/adapter-transformers) is an extension of HuggingFace's Transformers library, integrating adapters into state-of-the-art language models by incorporating AdapterHub, a central repository for pre-trained adapter modules. It is a drop-in replacement for transformers, which is regularly updated to stay up-to-date with the developments of transformers. +[adapters](https://github.com/adapter-hub/adapters) is an extension of HuggingFace's Transformers library, integrating adapters into state-of-the-art language models by incorporating AdapterHub, a central repository for pre-trained adapter modules. It is a drop-in replacement for transformers, which is regularly updated to stay up-to-date with the developments of transformers. Keywords: Adapters, LoRA, Parameter-efficient fine-tuning, Hub @@ -601,9 +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 Factory](https://github.com/hiyouga/LLaMA-Factory) -[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). +[LLaMA Factory](https://github.com/hiyouga/LLaMA-Factory) 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