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This is a Object Detection Answering model from TensorFlow Hub

This is a Object Detection Answering model from TensorFlow Hub

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.

This is a Image Classification model from PyTorch Hub

This is a Image Classification 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. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

This is an Image Classification model from PyTorch Hub. It takes an image as input and classifies the image to one of the 1000 classes.

This is a Object Detection Answering model from TensorFlow Hub

This is a Image Classification model from TensorFlow Hub

This is a Text Classification model from TensorFlow Hub

This is a Extractive Question Answering model from PyTorch Hub

This is a Image Classification model from TensorFlow Hub

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

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 TensorFlow Hub

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Product Description: Amazon Aurora Serverless v2 is an on-demand, auto-scaling configuration for Amazon Aurora that automatically adjusts database capacity based on application needs. It scales instantly to handle hundreds of thousands of transactions in a fraction of a second, providing the right amount of resources without manual intervention. This service supports both the MySQL-Compatible and PostgreSQL-Compatible editions of Aurora, offering high availability, performance, and resiliency.