---
license: apache-2.0
base_model: Qwen/Qwen3-1.7B
library_name: gguf
pipeline_tag: text-generation
language:
  - en
tags:
  - finance
  - personal-finance
  - information-extraction
  - transaction-extraction
  - gguf
  - ollama
  - qwen3
  - on-device
---

# WealthWise 1.7B (GGUF)

A compact, **on-device** model that extracts and classifies **financial
transactions** from SMS and email into structured JSON. Fine-tuned from
**Qwen3-1.7B** for the [WealthWise](https://github.com/iam-biswaraj/wealthwise)
local-first personal-finance app.

> 🚧 **Status: experimental / under active development.** WealthWise's larger
> **14B model is the most accurate today**; this 1.7B is the phone-sized variant
> that is **catching up**. On controlled benchmarks it already matches or beats
> the 14B; on the long tail of real-world mail it is still improving via
> distillation from the 14B teacher and user corrections. It is **~8× smaller and
> several× faster** and is intended for laptops, low-power machines, and mobile.

## What it does

Given a raw SMS or email message, it returns a single JSON object:

```json
{
  "amount": 437.0, "currency": "INR", "type": "debit",
  "merchant": "Swiggy - Behrouz Biryani", "account_last4": null,
  "date": "2026-06-12", "payment_method": "UPI", "reference": null,
  "balance": null, "is_recurring": false,
  "category_l1": "Food & Dining", "category_l2": "Food Delivery"
}
```

`category_l1` is one of: Food & Dining, Transportation, Shopping, Housing,
Utilities, Entertainment, Health, Education, Travel, Investments, Financial,
Income, Miscellaneous. Non-transactional messages return `{"is_transaction": false}`.

## Files
- `wealthwise-1.7b-q8_0.gguf` — Q8_0 quantized weights (~1.8 GB, near-lossless).
- `Modelfile` — Ollama recipe (correct **non-thinking** Qwen3 template + system prompt).

## Run it

### Ollama (recommended)
```bash
# from this folder:
ollama create wealthwise-1.7b -f Modelfile
ollama run wealthwise-1.7b
# or, if published to the Ollama registry:
# ollama pull codedrivehg/wealthwise-1.7b
```

Download the GGUF:
```bash
hf download codedrivehg/wealthwise-1.7b-GGUF --local-dir wealthwise-1.7b
```

### llama.cpp
```bash
llama-cli -m wealthwise-1.7b-q8_0.gguf -p "<your message>"
```

> **Important:** this model is trained for **non-thinking** output (direct JSON).
> The bundled `Modelfile` pre-fills the empty `<think></think>` block Qwen3
> expects — use it (or replicate that template) or the model may emit garbage.

## Training
- Base: `Qwen/Qwen3-1.7B` (Apache-2.0).
- Method: LoRA fine-tune (attention + MLP) on financial extraction data, then
  merged to 16-bit and exported to GGUF.
- Improving via knowledge **distillation** from the WealthWise 14B teacher (and a
  larger teacher), an expanding curated merchant database, and in-app corrections.

## Limitations
- Out-of-distribution real-world emails (unusual formats, multilingual, receipts
  with many line items) are where it still trails the 14B.
- Use the 14B for maximum accuracy on capable hardware.

## License
Apache-2.0 (inherits the Qwen3-1.7B base license).