PyTorch code and models for the DINOv2 self-supervised learning method.

Open-source evaluation toolkit of large vision-language models (LVLMs), support ~100 VLMs, 40+ benchmarks

Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilizatio…

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

TensorFlow/Keras port of Stable Diffusion

TensorRTx aims to implement popular deep learning networks with tensorrt network definition APIs

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

CoMoGAN: continuous model-guided image-to-image translation. CVPR 2021 oral.

ONVIF Client Implementation in Python 2+3 (using https://github.com/mvantellingen/python-zeep instead of suds as SOAP client)

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

TensorRT-7 Network Lib 包括常用目标检测、关键点检测、人脸检测、OCR等 可训练自己数据

YOLOv5 in PyTorch > ONNX > CoreML > iOS

oneflow documentation

A fork of Detectron2 with ResNeSt backbone

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

Latex code for making neural networks diagrams

High-resolution Networks for the Fully Convolutional One-Stage Object Detection (FCOS) algorithm

SSD-based object and text detection with Keras, SSD, DSOD, TextBoxes, SegLink, TextBoxes++, CRNN

Sublime Text 3 Windows 下拼音输入法支持

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

One has no future if one couldn't teach themself.

Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more)

记录Learning from data一书中的习题解答

TensorFlow Tutorial and Examples for Beginners with Latest APIs

Keras version of Realtime Multi-Person Pose Estimation project

Deformable Convolutional Networks