Sold by: Waltsoft Inc.
Deployed on AWS
XLM-RoBERTa Language Detector - 20-Language ID on SageMaker
Overview
Deploy XLM-RoBERTa Language Detection on Amazon SageMaker for accurate language identification across 20 languages. Essential for multilingual content pipelines, auto-routing translation workflows, and data quality filtering. 278MB, CPU-native, no GPU required. MIT licensed.
Highlights
- 278MB - detects 20 languages with 99%+ accuracy
- Essential for multilingual pipeline routing and translation gating
- No GPU required - real-time language ID for content moderation
Details
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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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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
XLM-RoBERTa Language Detector - 20-Language ID 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.
AWS infrastructure support
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