Sold by: Waltsoft Inc.
Deployed on AWS
Emotion Detector - 7-Class Sentiment Analysis for CX on SageMaker
Overview
Deploy DistilRoBERTa Emotion Detection on Amazon SageMaker for fine-grained 7-class emotion analysis: anger, disgust, fear, joy, neutral, sadness, surprise. At 83MB with no GPU required, it enables real-time CX analytics, mental health monitoring, and social media sentiment pipelines at scale. Apache-2.0 licensed.
Highlights
- 83MB 7-class emotion detection: anger, joy, fear, sadness and more
- Real-time CX analytics - works on reviews, tickets, and social posts
- No GPU required - fine-grained beyond positive/negative sentiment
Details
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Latest version
Deployed on AWS
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.10 |
ml.m5.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $0.10 |
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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
Initial release
Additional details
Inputs
- Summary
Emotion Detector - 7-Class Sentiment Analysis for CX on SageMaker
- Input MIME type
- application/json
https://waltsoft-marketplace-assets.s3.amazonaws.com/ml-validation/text-sample/sample.jsonl
https://waltsoft-marketplace-assets.s3.amazonaws.com/ml-validation/text-sample/sample.jsonl
Support
Vendor support
Contact support@waltsoft.net for deployment assistance.
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