---
license: apache-2.0
language:
  - en
tags:
  - document-intelligence
  - rag
  - extraction
  - enterprise
  - docwain
pipeline_tag: text-generation
base_model: muthugsubramanian/DocWain-14B-v2
---

# DocWain-14B-v2-unified (FP16)

DocWain is an **enterprise document intelligence agent** built for extraction,
analysis, comparison, and grounded response generation over user-uploaded
document profiles. This **unified** variant has identity, capability awareness,
and behavioural discipline (verbatim quoting, refusal on missing data, currency
preservation, anti-tailoring) baked into the weights via a focused LoRA SFT
finetune on synthetic data.

## What's in this release

- **Format:** FP16
- **Base model:** muthugsubramanian/DocWain-14B-v2 (vision-grafted Qwen3-14B)
- **Identity:** baked-in — model self-identifies as DocWain regardless of
  system prompt
- **Behaviour:** trained to quote verbatim from evidence, say "not specified
  in the documents" rather than fabricate, preserve currency symbols (₹/£/$),
  and refuse to add skills/education/experience that aren't in the source

## Capabilities

- Accurate extraction from invoices, contracts, resumes, policies, research
  papers, and other enterprise document types
- Document intelligence — summaries, key findings, cross-document
  relationships, anomaly surfacing
- Layout and context understanding — tables, charts, multi-page references
- Grounded response generation with verbatim quoting and explicit
  "not specified" handling
- Document generation — structured reports, comparison tables, executive
  briefs derived from the user's documents

## Training data

Synthetic-only per project policy. The training corpus contains:
- Identity / persona examples (no customer data)
- Capability awareness Q&A
- Synthetic invoices / contracts / resumes / research-paper snippets paired
  with ideal grounded responses
- Domain-mismatch refusal examples
- General-instruction mix-in to preserve breadth

No customer documents, no scraped private data.

## Recommended runtime

| Variant | Runtime | GPU floor |
|---------|---------|-----------|
| FP16 | vLLM, transformers | A100 80GB |
| AWQ INT4 | vLLM `--quantization compressed-tensors` | 16GB+ |
| GGUF Q5_K_M | Ollama / llama.cpp | 16GB GPU or CPU |
| GGUF Q4_K_M | Ollama / llama.cpp | 12GB GPU or CPU |

## Prompting

A short system prompt is enough at runtime — identity is in the weights:

```
You are DocWain — an enterprise document intelligence agent.
```

For full behaviour (RAG-aware, currency-preserving, anti-tailoring),
provide your standard DocWain system prompt; the model will respect both
its baked-in identity and the prompt-specified rules.
