Instructions to use Abiray/Qianfan-OCR-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Abiray/Qianfan-OCR-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Abiray/Qianfan-OCR-GGUF",
	filename="qianfan-ocr-4b-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "\"cats.jpg\""
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Abiray/Qianfan-OCR-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Abiray/Qianfan-OCR-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use Abiray/Qianfan-OCR-GGUF with Ollama:
```
ollama run hf.co/Abiray/Qianfan-OCR-GGUF:Q4_K_M
```

Unsloth Studio new

How to use Abiray/Qianfan-OCR-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Abiray/Qianfan-OCR-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Abiray/Qianfan-OCR-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Abiray/Qianfan-OCR-GGUF to start chatting

Pi new

How to use Abiray/Qianfan-OCR-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Abiray/Qianfan-OCR-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Abiray/Qianfan-OCR-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Abiray/Qianfan-OCR-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Abiray/Qianfan-OCR-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use Abiray/Qianfan-OCR-GGUF with Docker Model Runner:
```
docker model run hf.co/Abiray/Qianfan-OCR-GGUF:Q4_K_M
```

Lemonade

How to use Abiray/Qianfan-OCR-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Abiray/Qianfan-OCR-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qianfan-OCR-GGUF-Q4_K_M

List all available models

lemonade list

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

Downloads last month: 216

GGUF

Model size

4B params

Architecture

qwen3

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

Model tree for Abiray/Qianfan-OCR-GGUF

Base model

baidu/Qianfan-OCR

Quantized

(5)

this model

Paper for Abiray/Qianfan-OCR-GGUF

Qianfan-OCR: A Unified End-to-End Model for Document Intelligence

Paper • 2603.13398 • Published Mar 11 • 155