NaviDC-OCR GGUF Quantizations

Static GGUF quantizations of StarDoc-AI/NaviDC-OCR for high-speed local document parsing, formula recognition, table transcription, and structured Markdown OCR using llama.cpp.

NaviDC-OCR is a specialized document vision-language model trained to parse complex digital and camera-captured documents, extracting headings, body text, LaTeX math formulas, and Markdown tables with geometric precision.

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📊 Benchmark & Evaluation Results

Benchmarked on NVIDIA RTX GPU (CUDA) using llama-server on a complex technical document page containing headings, Schrödinger quantum equations, and multi-column tables:

Companion Multimodal Projector (mmproj):

• mmproj-NaviDC-OCR-F16.gguf (1.33 GB) — required for vision encoding alongside any language model quant.

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🚀 How to Run with llama.cpp

1. Start llama-server

llama-server \
  -m NaviDC-OCR-Q4_K_M.gguf \
  --mmproj mmproj-NaviDC-OCR-F16.gguf \
  --port 8090 \
  -ngl 99 \
  -c 4096

2. Query via OpenAI-compatible API

import requests, base64

with open("document_page.png", "rb") as f:
    img_b64 = base64.b64encode(f.read()).decode("utf-8")

response = requests.post(
    "http://127.0.0.1:8090/v1/chat/completions",
    json={
        "messages": [
            {
                "role": "user",
                "content": [
                    {"type": "text", "text": "Extract text."},
                    {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{img_b64}"}}
                ]
            }
        ],
        "max_tokens": 2048,
        "temperature": 0.0
    }
)

print(response.json()["choices"][0]["message"]["content"])

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📦 Files in this Repository

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💡 Acknowledgements & Citation

• Original Model: StarDoc-AI/NaviDC-OCR
• GGUF Conversion & Benchmarks: Pluto AI by @konradjr007