Alpa provides automatic parallelization for single-device neural network code across distributed clusters, supporting data, operator, and pipeline parallelism. It integrates with Jax, XLA, and Ray to deliver linear scaling for models with billions of parameters. The project offers a Hugging Face transformers-compatible interface for large model inference on distributed backends.