RESEARCH focuses on tutorials that have less to do with how to use the library but more about general research in
  transformers model
API contains the documentation of each public class and function, grouped in:
MAIN CLASSES for the main classes exposing the important APIs of the library.
MODELS for the classes and functions related to each model implemented in the library.
INTERNAL HELPERS for the classes and functions we use internally.
The library currently contains Jax, PyTorch and Tensorflow implementations, pretrained model weights, usage scripts and
conversion utilities for the following models.
Supported models
This list is updated automatically from the README with _make fix-copies_. Do not update manually! 
ALBERT (from Google Research and the Toyota Technological Institute at Chicago) released with the paper ALBERT: A Lite BERT for Self-supervised Learning of Language Representations, by Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut.
