Sold by: Waltsoft Inc.
Deployed on AWS
939K monthly downloads. 5-star sentiment scoring for English, German, French, Spanish, Italian, and Dutch. For global brand monitoring and CX analytics.
Overview
BERT-Base Multilingual Uncased Sentiment by NLPTown is a 5-class sentiment classifier trained on 110K product reviews in six European languages -- English, German, French, Spanish, Italian, and Dutch -- with 939K monthly downloads. Unlike binary positive/negative classifiers, it outputs granular 1-to-5 star ratings that map directly to Net Promoter Score calculations, CSAT analysis, and customer experience dashboards. Global e-commerce companies, brand monitoring platforms, and customer success teams use it to aggregate multilingual review sentiment without needing separate models per language. Deployed on SageMaker, it processes product reviews, survey responses, and support tickets from multi-language markets in a single inference call.
Highlights
- 5-star granular scoring maps directly to NPS, CSAT, and brand health dashboards
- Trained on 110K real product reviews in 6 European languages -- not translated, native training data
- 939K monthly downloads from global e-commerce, brand monitoring, and CX analytics teams
Details
Sold by
Delivery method
Latest version
Deployed on AWS
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Pricing
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.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 |
Vendor refund policy
No refunds.
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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
Initial release
Additional details
Inputs
- Summary
939K monthly downloads. 5-star sentiment scoring for English, German, French, Spanish, Italian, and Dutch. For global brand monitoring and CX analytics.
- 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.
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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