Allows for efficient training of large language models.
Utilizes parallel processing, thereby decreasing training time.
Capable of comprehending the context of natural language sentences.
Detects complex relationships within lengthy sentences.
Simple and consistent API for working with different transformer models, making it easy to experiment with different architectures and compare results.
Regularly updated with new models and features, making it a valuable resource for NLP researchers and practitioners.
Has support for both TensorFlow and PyTorch, making it easy to use with existing codebases and libraries.