BERT Base Uncased PyTorch Hub Sentence Pair Classification Discussions

This is a Sentence Pair Classification model built upon a Text Embedding model from [PyTorch Hub](https://pytorch.org/hub/huggingface_pytorch-transformers/ ). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies the second sentence entails the first sentence, and the no-entailment implies it does not. The Text Embedding model which is pre-trained on English Text returns an embedding of the input pair of sentences. The model available for deployment is created by attaching a binary classification layer to the output of the Text Embedding model, and then fine-tuning the entire model on [QNLI](https://rajpurkar.github.io/SQuAD-explorer/ ) dataset. When users leave BERT Base Uncased PyTorch Hub Sentence Pair Classification reviews, G2 also collects common questions about the day-to-day use of BERT Base Uncased PyTorch Hub Sentence Pair Classification. These questions are then answered by our community of 850k professionals. Submit your question below and join in on the G2 Discussion.