Sold by: Waltsoft Inc.
Deployed on AWS
facebook/bart-large-mnli on SageMaker. MNLI accuracy 89.9. Classify any text into any custom category set with zero training data -- tickets, contracts, documents. $0.10/hr flat.
Overview
facebook/bart-large-mnli is BART-large fine-tuned on the MultiNLI dataset, achieving 89.9% accuracy on MNLI matched evaluation. As a zero-shot classifier, it classifies text into any set of candidate labels without requiring labeled training data -- you provide the labels at inference time.
Deploy as a SageMaker endpoint to route customer support tickets, classify contract clauses, tag financial filings, or sort any document corpus into enterprise-defined taxonomies. Unlike supervised classifiers that require labeled training data and retraining for new categories, this model adapts to any label set instantly.
The endpoint accepts {"text": "...", "labels": ["billing", "technical", "refund", ...]} and returns a confidence score per label. Multi-label classification is supported. Typical latency is 0.3-0.6 seconds per classification on ml.m5.xlarge -- document this in your implementation guide for buyers who need real-time routing.
Primary use cases: customer support ticket routing, contract clause classification, financial document tagging, compliance screening against policy categories, and any supervised NLP task where building a labeled training set is not practical.
Highlights
- 89.9% MNLI accuracy -- classify any text into any label set with zero training data and zero labeled examples
- Instant taxonomy changes: add or remove categories at inference time, no retraining, no MLOps pipeline needed
- Flat $0.10/hr on ml.m5.xlarge -- no per-call charges, all data in your VPC, multi-label classification supported
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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.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Initial release
Additional details
Inputs
- Summary
facebook/bart-large-mnli on SageMaker. MNLI accuracy 89.9. Classify any text into any custom category set with zero training data -- tickets, contracts, documents. $0.10/hr flat.
- 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
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Contact support@waltsoft.net for deployment assistance.
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