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

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

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

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

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

A framework for few-shot evaluation of language models.

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

A python library for user-friendly forecasting and anomaly detection on time series.

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts

[ICLR 2026] RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning.

Official repo for consistency models.

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

Probabilistic time series modeling in Python

Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.

Scalable and user friendly neural 🧠 forecasting algorithms.

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

Vector (and Scalar) Quantization, in Pytorch

A highly efficient implementation of Gaussian Processes in PyTorch

A python library for self-supervised learning on images.

Learning in infinite dimension with neural operators.

[CVPR 2024 - Oral, Best Paper Award Candidate] Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation

Foundation Architecture for (M)LLMs

FFCV: Fast Forward Computer Vision (and other ML workloads!)

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods