Stars
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.
Fault tolerance for PyTorch (HSDP, LocalSGD, DiLoCo, Streaming DiLoCo)
Deep learning for dummies. All the practical details and useful utilities that go into working with real models.
Fast and memory-efficient exact attention
A fast implementation of T5/UL2 in PyTorch using Flash Attention
depyf is a tool to help you understand and adapt to PyTorch compiler torch.compile.
A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.
See https://github.com/cuda-mode/triton-index/ instead!
A PyTorch native platform for training generative AI models
Ring attention implementation with flash attention
Hackable and optimized Transformers building blocks, supporting a composable construction.
Repository for code used in the xVal paper
Fast & Simple repository for pre-training and fine-tuning T5-style models
fpocket is a very fast open source protein pocket detection algorithm based on Voronoi tessellation. The platform is suited for the scientific community willing to develop new scoring functions and…
FauxPilot - an open-source alternative to GitHub Copilot server
☁️ Terraform plugin for machine learning workloads: spot instance recovery & auto-termination | AWS, GCP, Azure, Kubernetes
High performance model preprocessing library on PyTorch
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Paper list for equivariant neural network
Plenoxels: Radiance Fields without Neural Networks
Officially unofficial re-implementation of paper: Paint Transformer: Feed Forward Neural Painting with Stroke Prediction, ICCV 2021.
Resource-adaptive cluster scheduler for deep learning training.
View part of your screen in grayscale or simulated color vision deficiency.
An all-atom protein structure dataset for machine learning.