Instructions to use openbmb/MiniCPM-OCR-Jev-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use openbmb/MiniCPM-OCR-Jev-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf openbmb/MiniCPM-OCR-Jev-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 openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf openbmb/MiniCPM-OCR-Jev-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 openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M

Use Docker

docker model run hf.co/openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use openbmb/MiniCPM-OCR-Jev-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openbmb/MiniCPM-OCR-Jev-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM-OCR-Jev-gguf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M

Ollama
How to use openbmb/MiniCPM-OCR-Jev-gguf with Ollama:
```
ollama run hf.co/openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use openbmb/MiniCPM-OCR-Jev-gguf with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M
```

Lemonade

How to use openbmb/MiniCPM-OCR-Jev-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull openbmb/MiniCPM-OCR-Jev-gguf:Q4_K_M

Run and chat with the model

lemonade run user.MiniCPM-OCR-Jev-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

GitHub · Usage

This repository hosts the GGUF build of MiniCPM-OCR Jev for llama.cpp. For the original weights and the full model card, see the base repository.

MiniCPM-OCR Jev (2B) scores OCR candidates for text, formula, and table regions, returning a quality score from 0 to 1.

Files

File	Size	Notes
`mmproj-model-f16.gguf`	0.671 GB	vision projector — required
`MiniCPM-OCR-Jev-F16.gguf`	3.776 GB	reference
`MiniCPM-OCR-Jev-Q8_0.gguf`	2.012 GB	near-lossless
`MiniCPM-OCR-Jev-Q6_K.gguf`	1.556 GB
`MiniCPM-OCR-Jev-Q5_K_M.gguf`	1.411 GB
`MiniCPM-OCR-Jev-Q5_K_S.gguf`	1.374 GB
`MiniCPM-OCR-Jev-Q5_1.gguf`	1.460 GB
`MiniCPM-OCR-Jev-Q5_0.gguf`	1.374 GB
`MiniCPM-OCR-Jev-Q4_K_M.gguf`	1.274 GB	smallest recommended
`MiniCPM-OCR-Jev-Q4_K_S.gguf`	1.212 GB
`MiniCPM-OCR-Jev-Q4_1.gguf`	1.288 GB
`MiniCPM-OCR-Jev-Q4_0.gguf`	1.202 GB
`MiniCPM-OCR-Jev-IQ4_XS.gguf`	1.202 GB	imatrix
`MiniCPM-OCR-Jev-IQ4_NL.gguf`	1.236 GB	imatrix
`MiniCPM-OCR-Jev-IQ3_M.gguf`	1.059 GB	imatrix
`MiniCPM-OCR-Jev-IQ3_XS.gguf`	1.027 GB	imatrix

Usage

llama-server \
  --model ./MiniCPM-OCR-Jev-Q8_0.gguf \
  --mmproj ./mmproj-model-f16.gguf \
  --host 0.0.0.0 --port 18498 \
  --ctx-size 40960 \
  --n-gpu-layers 999

Check verdict in the response — only scored means scoring actually ran.

Deployment details: llama.cpp guide for Jev.

Related checkpoints

Format	Hugging Face	ModelScope
BF16 (original)	🤗	ModelScope
GGUF (llama.cpp) (this repo)	🤗	ModelScope
AWQ W4A16	🤗	ModelScope
GPTQ W4A16	🤗	ModelScope

FAQ

Installation, model downloads, GPU memory, input formats, and unexpected outputs: FAQ.

License

Model weights, code, and documentation are released under the Apache License 2.0.

Downloads last month: -

GGUF

Model size

2B params

Architecture

qwen35

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for openbmb/MiniCPM-OCR-Jev-gguf

Base model

openbmb/MiniCPM-OCR-Jev

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(3)

this model

Collection including openbmb/MiniCPM-OCR-Jev-gguf

MiniCPM-OCR

Collection

Fast parsing. High accuracy. • 10 items • Updated about 7 hours ago • 9