Tags: #peft

A comprehensive framework from ModelScope for efficiently fine-tuning, evaluating, and deploying over 1000 large language models and multimodal large models using advanced techniques.

PEFT is a state-of-the-art library for Parameter-Efficient Fine-Tuning, drastically reducing the computational and storage costs of adapting large pretrained models.

Provides a collection of Colab notebooks for efficiently fine-tuning large language models using PEFT methods like LoRA and Hugging Face transformers.

A comprehensive code repository accompanying a hands-on course for mastering Huggingface Transformers, covering fundamental concepts to advanced fine-tuning and deployment techniques.

A beginner-friendly UI for fine-tuning language models using LoRA on commodity NVIDIA GPUs, though the project is no longer actively maintained.

An efficient toolkit for fine-tuning ChatGLM-6B models using PEFT methods, enabling customization and deployment of large language models.

A library implementing various parameter-efficient fine-tuning (PEFT) algorithms, including advanced LoRA variants, for Stable Diffusion models to enhance image generation.