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FLAX
Flexible neural network library for JAX
Apache-2.0
ABOUT
Training large neural networks in JAX requires writing complex training loops, managing model parameters and state, and handling distributed computation manually. Flax provides a high-level, modular API that abstracts away these complexities — offering pre-built layers, optimizers, checkpointing, and multi-device training support — so researchers can focus on model architecture and experimentation rather than infrastructure.
INSTALL
pip install flaxINTEGRATION GUIDE
1. Train large language models and transformers with distributed data parallelism across multiple GPUs/TPUs
2. Build and experiment with custom neural network architectures using a modular, functional API
3. Leverage JAX's JIT compilation and auto-differentiation for high-performance research prototyping
TAGS
jaxneural-networkdeep-learningtransformerresearchpython