Transformers: shared model, configuration and tokenizer interfaces

What changed

Unified pretrained NLP models, configuration serialization, model-specific tokenization and downstream workflows across PyTorch and TensorFlow in a reusable open-source library.

Scientific scope

Unified pretrained NLP models, configuration serialization, model-specific tokenization and downstream workflows across PyTorch and TensorFlow in a reusable open-source library. Original v1 has11named authors, not later expanded paper lists or every contributor to the living project. This is software access/integration, not invention of Transformer attention or all imported pretrained methods. Original2019 features and current library capabilities are separate.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Original v1 has11named authors, not later expanded paper lists or every contributor to the living project. This is software access/integration, not invention of Transformer attention or all imported pretrained methods. Original2019 features and current library capabilities are separate.

Contributors

• Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

• Transformers: State-of-the-art Natural Language Processing

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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