The multiprocessing module spins up multiple copies of the Python interpreter, each on a separate core, and provides primitives for splitting tasks across cores.

And Python’s support for multiprocessing is top-heavy: you have to spin up multiple copies of the Python runtime for each core and distribute your work between them.

Llama 2 API with multiprocessing The video tutorial below provides valuable insights into creating an API for the Llama 2 language model, with a focus on supporting multiprocessing with PyTorch.