🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Making large AI models cheaper, faster and more accessible

Train transformer language models with reinforcement learning.

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.

The official repo for “Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting”, ACL, 2025.

[EMNLP'23, ACL'24] To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

Awesome Pretrained Chinese NLP Models，高质量中文预训练模型&大模型&多模态模型&大语言模型集合

Muzic: Music Understanding and Generation with Artificial Intelligence

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

PyTorch original implementation of Cross-lingual Language Model Pretraining.

A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset

PythonLinearNonLinearControl is a library implementing the linear and nonlinear control theories in python.

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

The official code for “Deep Unrestricted Document Image Rectification”, TMM, 2023.

The official code for “DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction”, ACM MM, Oral Paper, 2021.

FABind: Fast and Accurate Protein-Ligand Binding (NeurIPS 2023)

BioT5 (EMNLP 2023) and BioT5+ (ACL 2024 Findings)

3D-RCNet: A 3D Relational Convolutional Network for Hyperspectral Image Classification

[CVPR 2025] 3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer

Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution Prediction" (NeurIPS-21)

A dual learning toolkit developed by Microsoft Research

SSM-DTA: Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction (Briefings in Bioinformatics 2023)

PyTorch code for KDD 2023 paper "Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design"

The official implementation of dual-view molecule pre-training.

MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion (ACL 2025)

Implementation of NeurIPS 2019 paper "Normalization Helps Training of Quantized LSTM"