DocWain-14B-v2-unified-AWQ

DocWain-14B-v2-unified (AWQ INT4 (W4A16) — for vLLM on 16GB GPU)

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: AWQ INT4 (W4A16) — for vLLM on 16GB GPU
• 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

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.