Results for “jamf”

High-performance numerical computing with JAX, covering functional transformations, Flax NNX, and best practices for ML research.

Provides guidance on using JAX for machine learning and mathematical analysis, covering core concepts, transformations, ML specifics, control flow, and parallelism.

Run GGUF models locally with llama.cpp, including finding the right file on the Hugging Face Hub, installing, quantizing, serving, and using Python bindings.