Stars
Models and examples built with TensorFlow
A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
A high-throughput and memory-efficient inference and serving engine for LLMs
OpenMMLab Detection Toolbox and Benchmark
π€ Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
State-of-the-art 2D and 3D Face Analysis Project
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Graph Neural Network Library for PyTorch
π¬ Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
π€ PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Datasets, Transforms and Models specific to Computer Vision
State-of-the-Art Text Embeddings
StyleGAN - Official TensorFlow Implementation
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
StyleGAN2 - Official TensorFlow Implementation
Tensorflow2.0 ππ is delicious, just eat it! ππ
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
Object detection, 3D detection, and pose estimation using center point detection:
Implementation of Graph Convolutional Networks in TensorFlow
Official code implementation of General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model
XLNet: Generalized Autoregressive Pretraining for Language Understanding
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Using the jedi autocompletion library for VIM.
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network (ECCV 2018)
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Keras implementation of RetinaNet object detection.