English | 简体中文 A unified, high-performance framework for training LLMs, VLMs, diffusion, and embodied models. 🌐 Website · 📖 Docs · ✍️ Blog · ⚡ Quick Start · 📊 Performance · 🏛️ Supported Models · 💬 Contact LoongForge is a unified training framework for LLMs, VLMs, diffusion, and embodied models, covering pre-training, continued pre-training, and SFT.
⚠️ Warning: Not Actively Maintained This repository is no longer actively maintained. For a more up-to-date alternative, please visit the LitGPT project: https://github.com/Lightning-AI/litgpt , which serves as the successor to this repository.
2025.12.09 Support Z-Image Turbo Standalone training is now supported. For details, please refer to the Standalone Environment Setup Repository.
This repo contains the source code of the Python package loralib and several examples of how to integrate it with PyTorch models, such as those in Hugging Face. See our paper for a detailed description of LoRA.
🤗 PEFT State-of-the-art Parameter-Efficient Fine-Tuning (PEFT) methods Fine-tuning large pretrained models is often prohibitively costly due to their scale. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters.
English | 简体中文 A unified, high-performance framework for training LLMs, VLMs, diffusion, and embodied models. 🌐 Website · 📖 Docs · ✍️ Blog · ⚡ Quick Start · 📊 Performance · 🏛️ Supported Models · 💬 Contact LoongForge is a unified training framework for LLMs, VLMs, diffusion, and embodied models, covering pre-training, continued pre-training, and SFT.
⚠️ Warning: Not Actively Maintained This repository is no longer actively maintained. For a more up-to-date alternative, please visit the LitGPT project: https://github.com/Lightning-AI/litgpt , which serves as the successor to this repository.
2025.12.09 Support Z-Image Turbo Standalone training is now supported. For details, please refer to the Standalone Environment Setup Repository.
This repo contains the source code of the Python package loralib and several examples of how to integrate it with PyTorch models, such as those in Hugging Face. See our paper for a detailed description of LoRA.
🤗 PEFT State-of-the-art Parameter-Efficient Fine-Tuning (PEFT) methods Fine-tuning large pretrained models is often prohibitively costly due to their scale. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters.