apple/axlearn

Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

An industrial extension library of pytorch to accelerate large scale model training

A Lightweight LLM Post-Training Library

Accelerate, Optimize performance with streamlined training and serving options with JAX.

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

Flax is a neural network library for JAX that is designed for flexibility.

An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries

Making large AI models cheaper, faster and more accessible

Named Tensors for Legible Deep Learning in JAX