Hugging Face's TensorFlow Philosophy
Hugging Face Blog
Hugging Face adopted four design philosophies for its TensorFlow implementation: models must be Keras objects with built-in loss functions, labels follow standard Keras conventions, and data pipelines integrate with the Hugging Face datasets library. The library allows users to load pretrained models in a single line of code—for example, `TFAutoModel.from_pretrained("bert-base-cased")`—and train them with standard Keras methods like `fit()` without writing custom training loops. This approach lets TensorFlow engineers leverage transfer learning and compose multiple pretrained models together while staying within familiar Keras abstractions.