Open-source Python framework for training and backtesting financial trading agents with deep reinforcement learning.
General-purpose toolkit implementing TLS, DTLS, and QUIC protocols on top of a standalone cryptographic library and CLI.
A library of model optimization techniques (quantization, pruning, distillation, NAS, speculative decoding, sparsity) that exports compressed checkpoints for inference frameworks.
An end-to-end open source platform for building and deploying machine learning models, with Python and C++ APIs.
Python library providing GPU-accelerated tensor computation like NumPy, plus a tape-based autograd system for building deep neural networks.