pretrained-models

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

Deezer source separation library including pretrained models.

👑 Easy-to-use and powerful NLP library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis and 🖼 Diffusion AIGC system etc.

A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)

Segmentation models with pretrained backbones. PyTorch.

Natural Language Processing Best Practices & Examples

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Model for All.

CodeGeeX: An Open Multilingual Code Generation Model

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

An open source implementation of CLIP.

A treasure chest for visual classification and recognition powered by PaddlePaddle

Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models

中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard

Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

Sandbox for training deep learning networks

Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.