Shypd.aiThe largest open index of AI toolsFlax is a neural network library for JAX that simplifies the creation, inspection, and debugging of neural networks. It offers a flexible API for researchers and developers working with JAX.
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Flax is a high-performance neural network library and ecosystem for JAX, designed with flexibility in mind. It allows users to experiment with new training methods by modifying the training loop rather than adding features to a rigid framework. Developed in close collaboration with the JAX team, Flax provides a comprehensive set of tools for neural network research, including a neural network API (flax.nnx) with components like Linear, Conv, BatchNorm, and Attention. It also offers utilities for replicated training, serialization, checkpointing, metrics, and device prefetching. Educational examples, such as MNIST and inference with the Gemma language model, are included to help users get started quickly. The new Flax NNX API, released in 2024, further simplifies neural network creation, inspection, debugging, and analysis by supporting Python reference semantics, enabling reference sharing and mutability.
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