Sold by: Sigmodata
Deployed on AWS
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SageMaker model package for detecting emotions in English text
Overview
This SageMaker model package provides a REST API to detect the dominant emotion in English text.
Each input text is classified into one of six emotions: sadness, joy, love, anger, fear, or surprise, with a confidence score. Use it for customer feedback analysis, social listening, or conversational analytics.
The API accepts input as JSON or CSV and supports real-time endpoints and batch transform.
We welcome your feedback at aws-support@sigmodata.com
Highlights
- Classifies text into six emotions: sadness, joy, love, anger, fear, surprise.
- Fine-tuned ModernBERT transformer served with ONNX Runtime for fast, low-cost inference.
- Supports JSON and CSV input, real-time endpoints and SageMaker batch transform.
Details
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Deployed on AWS
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $0.10 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $0.10 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $0.10 |
ml.c5.2xlarge Inference (Real-Time) | Model inference on the ml.c5.2xlarge instance type, real-time mode | $0.10 |
ml.c5.xlarge Inference (Batch) | Model inference on the ml.c5.xlarge instance type, batch mode | $0.10 |
ml.c5.xlarge Inference (Real-Time) | Model inference on the ml.c5.xlarge instance type, real-time mode | $0.10 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.10 |
ml.m5.2xlarge Inference (Real-Time) | Model inference on the ml.m5.2xlarge instance type, real-time mode | $0.10 |
ml.m5.xlarge Inference (Batch) | Model inference on the ml.m5.xlarge instance type, batch mode | $0.10 |
ml.m5.xlarge Inference (Real-Time) | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.10 |
Vendor refund policy
No refunds offered but you may cancel at any time
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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
- First release
- JSON and CSV input and output
- ModernBERT fine-tuned model served with ONNX Runtime
Additional details
Inputs
- Summary
A JSON object with a "texts" array of strings to classify (or a CSV file, one text per line, for batch transform).
- Input MIME type
- text/csv, application/json
{"texts": ["I am so happy today everything is going great"]}
I am so happy today everything is going great
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
texts | List of text strings to classify | - | Yes |
Support
Vendor support
contact: support@sigmodata.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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SageMaker model package for Sentiment Analysis
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