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Product Description
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.
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Product Description
This is a Extractive Question Answering model from PyTorch Hub
Product Description
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.
Product Description
This is a Image Classification model from TensorFlow Hub
Product Description
This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub
Product Description
This is a Sentence Pair Classification model built upon a Text Embedding model from TensorFlow Hub
Product Description
This is a Image Classification model from TensorFlow Hub
Product Description
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.
Product Description
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.
Product Description
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.
Product Description
This is a Object Detection Answering model from TensorFlow Hub
Product Description
This is a Image Classification model from TensorFlow Hub
Product Description
This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub
Product Description
This is a Object Detection Answering model from TensorFlow Hub
Product Description
This is a Object Detection Answering model from TensorFlow Hub
Product Description
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. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.
Product Description
This is a Image Classification model from TensorFlow Hub
Product Description
This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub
Product Description
It takes an image as input and returns bounding boxes for the objects in the image. The model is pre-trained on COCO 2017 which comprises images with multiple objects and the task is to identify the objects and their positions in the image. A list of the objects that the model can identify is given at the end of the page. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc
Product Description
This is a Object Detection Answering model from TensorFlow Hub
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