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README.md

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+---
+license: gemma
+base_model: google/functiongemma-270m-it
+tags:
+  - function-calling
+  - finance
+  - sms-parsing
+  - transaction-extraction
+  - gguf
+  - llama-cpp
+language:
+  - en
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# FunctionGemma Bank SMS Parser
+
+A fine-tuned [FunctionGemma-270M-IT](https://huggingface.co/google/functiongemma-270m-it) model for extracting structured transaction data from bank SMS messages.
+
+## Model Description
+
+This model is trained to perform two functions:
+
+1. **`extract_transaction`** - Parse banking SMS and extract structured fields:
+   - `source`: Bank or sender name
+   - `currency`: Currency code (INR, USD, etc.)
+   - `amount`: Transaction amount (number)
+   - `date`: Transaction date
+   - `destination`: Recipient or merchant
+   - `type`: "debit" or "credit"
+
+2. **`skip_message`** - Identify non-transaction messages:
+   - OTPs and verification codes
+   - Promotional messages
+   - Payment requests (not completed transactions)
+   - Account alerts without transactions
+
+## Quantization Options
+
+| File | Quantization | Size | Description |
+|------|--------------|------|-------------|
+| `functiongemma-270m-bank-sms-parser-Q4_K_M.gguf` | Q4_K_M | ~242MB | **Recommended** - Best size/quality tradeoff |
+| `functiongemma-270m-bank-sms-parser-Q5_K_M.gguf` | Q5_K_M | ~248MB | Higher quality if Q4 shows issues |
+| `functiongemma-270m-bank-sms-parser-Q8_0.gguf` | Q8_0 | ~280MB | Near-lossless, for validation |
+
+## Usage
+
+### With llama.cpp server
+
+```bash
+# Download model
+huggingface-cli download kartikaybagla/functiongemma-bank-sms-parser \
+    functiongemma-270m-bank-sms-parser-Q4_K_M.gguf \
+    --local-dir ./models
+
+# Run server
+llama-server --model ./models/functiongemma-270m-bank-sms-parser-Q4_K_M.gguf \
+    --host 0.0.0.0 --port 8080 --ctx-size 2048
+```
+
+### With Docker
+
+```bash
+docker run -p 8080:8080 -v ./models:/models \
+    ghcr.io/ggml-org/llama.cpp:server \
+    --model /models/functiongemma-270m-bank-sms-parser-Q4_K_M.gguf \
+    --host 0.0.0.0 --port 8080
+```
+
+### API Request
+
+```bash
+curl http://localhost:8080/v1/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "prompt": "<bos><start_of_turn>developer\nYou are a financial transaction extractor. Analyze SMS messages and:\n1. If the message describes a completed financial transaction (money sent, received, debited, or credited), use extract_transaction to capture the details.\n2. If the message is not a transaction (OTP, promotional, application status, payment request, etc.), use skip_message.\n\nOnly extract actual completed transactions with concrete amounts, not payment requests or pending transactions.<start_function_declaration>declaration:extract_transaction{description:<escape>Extract transaction details from a banking SMS message<escape>,parameters:{properties:{source:{type:<escape>STRING<escape>},currency:{type:<escape>STRING<escape>},amount:{type:<escape>NUMBER<escape>},date:{type:<escape>STRING<escape>},destination:{type:<escape>STRING<escape>},type:{type:<escape>STRING<escape>}},required:[<escape>source<escape>,<escape>currency<escape>,<escape>amount<escape>,<escape>date<escape>,<escape>destination<escape>,<escape>type<escape>],type:<escape>OBJECT<escape>}}<end_function_declaration><start_function_declaration>declaration:skip_message{description:<escape>Skip messages that are not financial transactions<escape>,parameters:{properties:{reason:{type:<escape>STRING<escape>}},required:[<escape>reason<escape>],type:<escape>OBJECT<escape>}}<end_function_declaration><end_of_turn>\n<start_of_turn>user\nICICI Bank Acct XX123 debited Rs 450.00 on 15-Jan-25; UPI to SWIGGY. UPI Ref: 123456789012<end_of_turn>\n<start_of_turn>model\n",
+    "max_tokens": 200,
+    "stop": ["<end_function_call>"]
+  }'
+```
+
+### Example Output
+
+**Input SMS:**
+```
+ICICI Bank Acct XX123 debited Rs 450.00 on 15-Jan-25; UPI to SWIGGY. UPI Ref: 123456789012
+```
+
+**Model Output:**
+```
+<start_function_call>extract_transaction{"source": "ICICI Bank", "currency": "INR", "amount": 450.00, "date": "15-Jan-25", "destination": "SWIGGY", "type": "debit"}<end_function_call>
+```
+
+**Input SMS (non-transaction):**
+```
+Your OTP for login is 482910. Valid for 5 minutes. Do not share.
+```
+
+**Model Output:**
+```
+<start_function_call>skip_message{"reason": "OTP verification code"}<end_function_call>
+```
+
+## Training
+
+- **Base Model**: [google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it)
+- **Training Framework**: Hugging Face TRL (SFTTrainer)
+- **Training Data**: Classified bank SMS messages from Indian banks
+- **Fine-tuning Method**: LoRA
+
+## Intended Use
+
+This model is designed for:
+- Personal finance automation
+- Importing transactions into budgeting apps (e.g., Actual Budget)
+- SMS-based expense tracking
+
+## Limitations
+
+- Primarily trained on Indian bank SMS formats (ICICI, HDFC, SBI, etc.)
+- May not generalize well to banks from other countries
+- Requires the specific prompt format shown above
+- Not suitable for security-critical applications without additional validation
+
+## License
+
+This model inherits the [Gemma license](https://ai.google.dev/gemma/terms) from the base model.
+
+## Links
+
+- [Project Repository](https://github.com/kartikaybagla/bank-sms-parsing)
+- [Base Model](https://huggingface.co/google/functiongemma-270m-it)