Awesome GitHub RepositoriesMulti-Modal Data Processing

Align-anything is a multi-modal large language model alignment framework designed to fine-tune models across text, image, video, and audio. It functions as a distributed training orchestrator and toolkit for implementing preference-based learning to ensure model behaviors match human intentions and values. The framework provides specialized pipelines for Supervised Fine-Tuning and Direct Preference Optimization. It includes a high-performance inference engine wrapper for actor models to reduce sequence generation time and a dedicated training environment for refining vision-language-action mo

FlagAI is a distributed deep learning framework and platform designed for the end-to-end lifecycle of large-scale foundation models. It provides a toolkit for training, fine-tuning, and deploying large language models and multi-modal systems across multi-node computing clusters. The project features hardware-agnostic compute abstractions to ensure consistent execution across different accelerators. It includes a dedicated library for parameter-efficient fine-tuning, allowing large neural networks to be adapted to specific tasks with minimal parameter updates and reduced computational overhead

mmpretrain is a modular PyTorch computer vision framework designed for developing, training, and benchmarking deep learning architectures. It serves as a comprehensive toolkit for vision tasks, providing a specialized platform for multimodal machine learning and self-supervised learning. The project features a computer vision model zoo containing architectural definitions and pre-trained weights for backbones such as ViT, ConvNeXt, and Swin Transformer. It distinguishes itself through a dedicated self-supervised learning toolkit that implements algorithms like MAE and DINO to train models wit