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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/distilbert-base-multilingual-cased
Details
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Delivery method
Latest version
Deployed on AWS
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $0.00 |
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $0.00 |
ml.m5.xlarge Inference (Real-Time) | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.00 |
ml.c5.xlarge Inference (Real-Time) | Model inference on the ml.c5.xlarge instance type, real-time mode | $0.00 |
ml.c5.2xlarge Inference (Real-Time) | Model inference on the ml.c5.2xlarge instance type, real-time mode | $0.00 |
ml.g4dn.xlarge Inference (Real-Time) | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $0.00 |
ml.p2.xlarge Inference (Real-Time) | Model inference on the ml.p2.xlarge instance type, real-time mode | $0.00 |
ml.p3.2xlarge Inference (Real-Time) | Model inference on the ml.p3.2xlarge instance type, real-time mode | $0.00 |
ml.m5.xlarge Inference (Batch) | Model inference on the ml.m5.xlarge instance type, batch mode | $0.00 |
ml.c5.xlarge Inference (Batch) | Model inference on the ml.c5.xlarge instance type, batch mode | $0.00 |
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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.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
This CPU version supports model run on CPU instance types
Additional details
Inputs
- Summary
The input is a pair of sentences.
- 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
Resources
Vendor resources
Support
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