- Hong Kong
- https://lzhengisme.github.io/
Stars
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
A toolkit for developing and comparing reinforcement learning algorithms.
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
Official inference repo for FLUX.1 models
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
DALL·E Mini - Generate images from a text prompt
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RN…
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
The RedPajama-Data repository contains code for preparing large datasets for training large language models.
Meta Lingua: a lean, efficient, and easy-to-hack codebase to research LLMs.
[COLM 2024] OpenAgents: An Open Platform for Language Agents in the Wild
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
Release for Improved Denoising Diffusion Probabilistic Models
A deep learning library for video understanding research.
Simple and easily configurable grid world environments for reinforcement learning
Repository for Meta Chameleon, a mixed-modal early-fusion foundation model from FAIR.
🚀 Efficient implementations of state-of-the-art linear attention models in Torch and Triton
[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings
Pytorch library for fast transformer implementations
The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts".