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This is a Sentence Pair Classification model built upon a Text Embedding model from Hugging Face
Overview
This is a Sentence Pair Classification model built upon a Text Embedding model from Hugging Face . 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.
Highlights
- This is a Sentence Pair Classification model from Hugging Face: https://huggingface.co/bert-large-uncased-whole-word-masking
Details
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
This GPU version supports model run on GPU instance types
Additional details
Inputs
- Summary
The input is a pair of paragraphs
- Input MIME type
- application/list-text
https://github.com/aws-samples/aws-marketplace-machine-learning/blob/master/using_open_source_model_packages/HF_spc_model/input_example
https://github.com/aws-samples/aws-marketplace-machine-learning/blob/master/using_open_source_model_packages/HF_spc_model/input_example
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