Model Card for Qianfan-OCR-4B-GGUF
This repository contains GGUF format quantizations (Q4_K_M, Q5_K_M, Q6_K, Q8_0) of Qianfan-OCR, a 4B-parameter end-to-end document intelligence model developed by the Baidu Qianfan Team. It unifies document parsing, layout analysis, and document understanding within a single vision-language architecture.
Model Details
Model Description
Qianfan-OCR is designed to replace traditional multi-stage OCR pipelines. Instead of chaining separate layout detection and text recognition modules, it performs direct image-to-Markdown conversion. It introduces Layout-as-Thought, an optional thinking phase where the model generates structured layout representations before producing the final output.
- Developed by: Baidu Qianfan Team
- Shared by: Abhiray
- Model type: Multimodal Vision-Language Model (VLM)
- Text Backbone: Qwen3-4B
- Vision Encoder: Qianfan-ViT (AnyResolution up to 4K)
- Language(s) (NLP): Multilingual (192 languages supported)
- License: Apache-2.0
Model Sources
- Repository: Baidu Qianfan-OCR
- Paper: Qianfan-OCR: A Unified End-to-End Model for Document Intelligence
Uses
Direct Use
- Document Parsing: High-fidelity Image-to-Markdown conversion.
- Table/Formula Recognition: Extracting complex tables (merged cells) and LaTeX formulas.
- Key Information Extraction (KIE): Structured data extraction from receipts, invoices, and IDs.
- Visual Question Answering (DocVQA): Reasoning over charts, graphs, and structured documents.
Out-of-Scope Use
- The model is not intended for generating creative fiction or conversational roleplay; it is optimized for high-accuracy document intelligence and visual grounding.
How to Get Started with the Model
1. Requirements
You need both a Quantized Model File (.gguf) and the Vision Projector (qianfan-ocr-mmproj.gguf).
2. Running with Koboldcpp (Recommended)
./koboldcpp \
--model qianfan-ocr-4b-Q4_K_M.gguf \
--mmproj qianfan-ocr-mmproj.gguf \
--usecuda 0 \
--gpulayers 99 \
--contextsize 8192 \
--remotetunnel
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Base model
baidu/Qianfan-OCR