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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.

This is a Object Detection Answering model from TensorFlow 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.

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 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 Object Detection Answering model from PyTorch Hub

This is a Image Classification model from TensorFlow Hub

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

This is a Extractive Question Answering 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.

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.

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.

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

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.

This is a Image Classification model from PyTorch Hub

This is a Image Classification model from TensorFlow Hub

This is a Image Classification model from TensorFlow Hub

The Microsoft Windows Server 2016 Base for STIG compliance is an Amazon Machine Image offered by Amazon Web Services . This AMI provides a secure and reliable environment for deploying applications using the Microsoft Web Platform on AWS's high-performance cloud infrastructure. It is pre-configured to meet the Security Technical Implementation Guide standards, ensuring compliance with stringent security protocols. Key Features and Functionality: - STIG Compliance: The AMI is configured accord