Stars
🤗 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.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Streamlit — A faster way to build and share data apps.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Federated query engine for AI - The only MCP Server you'll ever need
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
OpenMMLab Detection Toolbox and Benchmark
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source …
Graph Neural Network Library for PyTorch
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
End-to-End Object Detection with Transformers
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
Image augmentation for machine learning experiments.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Python Implementation of Reinforcement Learning: An Introduction
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Ongoing research training transformer models at scale
Open deep learning compiler stack for cpu, gpu and specialized accelerators