🤗 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.

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

JSON for Modern C++

TensorFlow code and pre-trained models for BERT

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Visualizer for neural network, deep learning and machine learning models

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

This repository is no longer maintained.

This repository contains implementations and illustrative code to accompany DeepMind publications

Python Imaging Library (Fork)

An open source implementation of CLIP.

Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3, Qwen3-MoE, DeepSeek-R1, GLM4.5, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Llava, …

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

A collection of resources and papers on Diffusion Models

OneDrive Client for Linux

Unsupervised text tokenizer for Neural Network-based text generation.

🤘 awesome-semantic-segmentation

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

Best Practices, code samples, and documentation for Computer Vision.

BertViz: Visualize Attention in Transformer Models

Using Low-rank adaptation to quickly fine-tune diffusion models.

An annotated implementation of the Transformer paper.

open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

『ゼロから作る Deep Learning』(O'Reilly Japan, 2016)