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--- |
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license: mit |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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tags: |
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- banking |
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- sms |
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- json |
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- parser |
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- financial |
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- india |
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datasets: |
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- synthetic |
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widget: |
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- example_title: "Transaction SMS" |
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text: "Sent Rs.1500.00 from HDFC Bank AC XX1234 to john@okicici on 15-Aug-25.UPI Ref 123456789012." |
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- example_title: "Credit SMS" |
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text: "Rs.25000 credited to your SBI Bank a/c XX5678 via NEFT from beneficiary COMPANY LTD." |
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--- |
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# Banking SMS JSON Parser V8 |
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Advanced AI model that converts Indian banking SMS messages into structured JSON format. |
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## Features |
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- ✅ Detects transaction vs non-transaction messages |
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- ✅ Extracts amount, date, transaction type, last 4 digits |
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- ✅ Categorizes transactions into 32+ categories |
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- ✅ Handles unknown merchants with "Other" category |
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- ✅ Supports UPI, NEFT, RTGS, Card transactions |
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- ✅ 60,000+ training samples with realistic Indian banking patterns |
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## Usage |
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## Training Data |
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- 60,000 training samples |
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- 6,000 validation samples |
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- 75% transaction, 25% non-transaction messages |
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- Realistic Indian banking SMS patterns |
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- Major Indian banks: ICICI, HDFC, SBI, Kotak, Axis, BOB, YES, etc. |
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## Performance |
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Optimized for high accuracy on real-world Indian banking SMS messages with proper category classification and transaction detection. |
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