The latest release v5.20.2 has been published in the huggingface/transformers repository on GitHub. This repository is a Python framework that gathers the definitions of text, image, audio, video, and multimodal models in one place and makes those definitions usable in both inference and training. The part where a model is defined in code is the core of this library.
The role of this repository is to connect different training frameworks and inference engines so that they share the same model definitions. It is about making a definition declared on one side loadable and usable on the other. Model definitions that handle not only text but also audio and video, and images, go into the same framework.
The README states that this framework requires Python and PyTorch, and guides through both package installation and installation from source. The repository contains documentation related to model definitions and READMEs in several languages. This repository was created on October 29, 2018, has 167931 stars, and is licensed under Apache-2.0.
However, the provided record contains no scores for the novelty, technology, and quality categories; only the momentum score of 6.8 out of 10 remains. No performance comparison figures or change list for v5.20.2 are given either, so it cannot be confirmed what this release changed. Since the only score category is momentum, it is difficult to judge whether to adopt this repository as the standard right away.