Deep Learning Frameworks in Production — PyTorch, TensorFlow, JAX, and HuggingFace¶
Every model in Part X of this book eventually has to run on top of one of four frameworks, and the choice is rarely made by a research paper — it is made by what the training cluster, the serving stack, and the team's muscle memory already commit you to. PyTorch dominates research and most production training; TensorFlow still guards a decade of enterprise pipelines you will inherit, not choose; JAX wins the narrow but real set of workloads where functional composition and TPU-native XLA compilation pay for themselves; and the HuggingFace stack has become the de facto packaging layer that ships models between all three. …
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