We write your reusable computer vision tools. 💜
Repository Index
47,133 repositories indexed
1–24 of 26 · Most stars
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
pix2tex: Using a ViT to convert images of equations into LaTeX code.
A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature.
Convert Machine Learning Code Between Frameworks
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
Low-code framework for building custom LLMs, neural networks, and other AI models
Fast and Accurate ML in 3 Lines of Code
:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
🛠 All-in-one web-based IDE specialized for machine learning and data science.
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
World's first general purpose 3D object detection codebse.
An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI Artifact.
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
Local AI BGM and sound effects for Claude Code and any MCP client. Stable Audio 3 on Apple Silicon (MLX) and Windows NVIDIA GPUs (PyTorch). No cloud, no API key.
LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation
Code for PaperRobot: Incremental Draft Generation of Scientific Ideas
Deep and Machine Learning for Microscopy