21st century AD

Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

Keybase Go Library, Client, Service, OS X, iOS, Android, Electron

Gevulot is an internet scale compute network for zero-knowledge proof generation and verification.

Specification of the Farcaster Protocol

A Data Streaming Library for Efficient Neural Network Training

Not HDF5

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.

Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch

ONNX Runtime in Cairo 1.0 for verifiable ML inference using STARK

Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activelo…

✨ 🐍 Python SDK for Starknet.

Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.

Block the face of Donald Trump on the Web

A Python package to manage extremely large amounts of data

🚴 Call stack profiler for Python. Shows you why your code is slow!

A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.

Xournal++ is a handwriting notetaking software with PDF annotation support. Written in C++ with GTK3, supporting Linux (e.g. Ubuntu, Debian, Arch, SUSE), macOS and Windows 10. Supports pen input fr…

Enabling PyTorch on XLA Devices (e.g. Google TPU)

Concise deep learning for JAX

Named Tensor implementation for Torch

Numpy group_by and set-operations

Turn Python scripts into handouts with Markdown and figures

Training Transformer-XL on 128 GPUs

Lightweight interface to AWS

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

Hierarchy-based Image Embeddings for Semantic Image Retrieval

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)