Features
Easy-to-use state-of-the-art models:
High performance on natural language understanding & generation, computer vision, and audio tasks.
Low barrier to entry for educators and practitioners.
Few user-facing abstractions with just three classes to learn.
A unified API for using all our pretrained models.
Lower compute costs, smaller carbon footprint:
Researchers can share trained models instead of always retraining.
Practitioners can reduce compute time and production costs.
Dozens of architectures with over 20,000 pretrained models, some in more than 100 languages.
Choose the right framework for every part of a model's lifetime:
Train state-of-the-art models in 3 lines of code.
Move a single model between TF2.0/PyTorch/JAX frameworks at will.
Seamlessly pick the right framework for training, evaluation and production.
