78 lines
2.6 KiB
Markdown
78 lines
2.6 KiB
Markdown
---
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license: apache-2.0
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language:
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- en
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tags:
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- document-intelligence
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- rag
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- extraction
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- enterprise
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- docwain
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pipeline_tag: text-generation
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base_model: muthugsubramanian/DocWain-14B-v2
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---
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# DocWain-14B-v2-unified (FP16)
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DocWain is an **enterprise document intelligence agent** built for extraction,
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analysis, comparison, and grounded response generation over user-uploaded
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document profiles. This **unified** variant has identity, capability awareness,
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and behavioural discipline (verbatim quoting, refusal on missing data, currency
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preservation, anti-tailoring) baked into the weights via a focused LoRA SFT
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finetune on synthetic data.
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## What's in this release
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- **Format:** FP16
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- **Base model:** muthugsubramanian/DocWain-14B-v2 (vision-grafted Qwen3-14B)
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- **Identity:** baked-in — model self-identifies as DocWain regardless of
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system prompt
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- **Behaviour:** trained to quote verbatim from evidence, say "not specified
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in the documents" rather than fabricate, preserve currency symbols (₹/£/$),
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and refuse to add skills/education/experience that aren't in the source
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## Capabilities
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- Accurate extraction from invoices, contracts, resumes, policies, research
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papers, and other enterprise document types
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- Document intelligence — summaries, key findings, cross-document
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relationships, anomaly surfacing
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- Layout and context understanding — tables, charts, multi-page references
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- Grounded response generation with verbatim quoting and explicit
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"not specified" handling
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- Document generation — structured reports, comparison tables, executive
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briefs derived from the user's documents
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## Training data
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Synthetic-only per project policy. The training corpus contains:
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- Identity / persona examples (no customer data)
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- Capability awareness Q&A
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- Synthetic invoices / contracts / resumes / research-paper snippets paired
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with ideal grounded responses
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- Domain-mismatch refusal examples
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- General-instruction mix-in to preserve breadth
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No customer documents, no scraped private data.
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## Recommended runtime
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| Variant | Runtime | GPU floor |
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|---------|---------|-----------|
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| FP16 | vLLM, transformers | A100 80GB |
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| AWQ INT4 | vLLM `--quantization compressed-tensors` | 16GB+ |
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| GGUF Q5_K_M | Ollama / llama.cpp | 16GB GPU or CPU |
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| GGUF Q4_K_M | Ollama / llama.cpp | 12GB GPU or CPU |
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## Prompting
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A short system prompt is enough at runtime — identity is in the weights:
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```
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You are DocWain — an enterprise document intelligence agent.
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```
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For full behaviour (RAG-aware, currency-preserving, anti-tailoring),
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provide your standard DocWain system prompt; the model will respect both
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its baked-in identity and the prompt-specified rules.
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