Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
ELECTRA-Small++
Latest Version:
CPU
This is a Text Classification model from TensorFlow Hub
Product Overview
This is a Text Classification model built upon a Text Embedding model from [TensorFlow Hub](https://tfhub.dev/google/electra_small/1 ). 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.
Key Data
Version
Type
Model Package
Highlights
This is an Text Classification model from TensorFlow Hub: https://tfhub.dev/google/electra_small/1
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$0.00/hr
running on ml.m5.xlarge
Model Batch Transform$0.00/hr
running on ml.m5.xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$0.23/host/hr
running on ml.m5.xlarge
SageMaker Batch Transform$0.23/host/hr
running on ml.m5.xlarge
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
|---|---|---|
ml.m5.xlarge Vendor Recommended | $0.00 | |
ml.c5.xlarge | $0.00 | |
ml.c5.2xlarge | $0.00 |
Usage Information
Model input and output details
Input
Summary
The input is a pair of paragraphs
Input MIME type
application/x-textSample input data
Output
Summary
The output is a JSON object containing the logits corresponding to the classes: "negative sentiment" and "positive sentiment".
Output MIME type
application/jsonSample output data
Sample notebook
Additional Resources
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Support Information
AWS Infrastructure
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