Hugging Face 的 TensorFlow 哲學：打造無縫的雙框架 AI 生態系
Original: Hugging Face's TensorFlow Philosophy
Although Hugging Face originally got its start with PyTorch at its core (formerly known as `pytorch-transformers`), as the community grew…
Hugging Face 闡述了其對 TensorFlow (TF) 的核心哲學：將 TF 視為一等公民，確保與 PyTorch 模型的雙向互操作性。透過將 TF 模型設計為 `tf.keras.Model` 的子類別，開發者能直接使用 Keras 的 `fit()` 等 API，並支援 XLA 編譯與 `tf.data`，為 TF 社群提供無縫且直覺的開發體驗。
Although Hugging Face originally got its start with PyTorch at its core (formerly known as `pytorch-transformers`), as the community grew, they recognized the diversity of the machine learning ecosystem. Rather than letting framework choice limit developers' creativity, Hugging Face committed to elevating TensorFlow to the status of a "first-class citizen" on par with PyTorch. This blog post elaborates on the core philosophy guiding their TensorFlow support:
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