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This is a Object Detection Answering model from TensorFlow Hub

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

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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 and Romanian 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

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

This is a Extractive Question Answering model from PyTorch Hub

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 sentenc

This is a Image Classification model from TensorFlow Hub

It takes as input a pair of question-context strings, and returns a sub-string from the context as a answer to the question. The Text Embedding model which is pre-trained on English Text returns an embedding of the input pair of question-context strings. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

It takes a text string as input and classifies the input text as either a positive or negative movie review. The Text Embedding model which is pre-trained on MEDLINE/PubMed returns an embedding of the input text. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet-21k which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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 WikiPedia and BookCorpus returns an embedding of the input pair of sentences. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

This is a Sentence Pair Classification model built upon a Text Embedding model from TensorFlow Hub

This is a Image Classification model from TensorFlow Hub

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

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It takes as input a pair of question-context strings, and returns a sub-string from the context as a answer to the question. The Text Embedding model which is pre-trained on English Text returns an embedding of the input pair of question-context strings. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.