Instructions to use openbmb/MiniCPM-OCR-1.0-DSpark-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-1.0-DSpark-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-1.0-DSpark-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf openbmb/MiniCPM-OCR-1.0-DSpark-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-1.0-DSpark-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Use Docker

docker model run hf.co/openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use openbmb/MiniCPM-OCR-1.0-DSpark-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-1.0-DSpark-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM-OCR-1.0-DSpark-gguf",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Ollama
How to use openbmb/MiniCPM-OCR-1.0-DSpark-gguf with Ollama:
```
ollama run hf.co/openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M
```
Unsloth Desktop

How to use openbmb/MiniCPM-OCR-1.0-DSpark-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use openbmb/MiniCPM-OCR-1.0-DSpark-gguf with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M
```

Lemonade

How to use openbmb/MiniCPM-OCR-1.0-DSpark-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Run and chat with the model

lemonade run user.MiniCPM-OCR-1.0-DSpark-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use openbmb/MiniCPM-OCR-1.0-DSpark-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf openbmb/MiniCPM-OCR-1.0-DSpark-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 openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use openbmb/MiniCPM-OCR-1.0-DSpark-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "openbmb/MiniCPM-OCR-1.0-DSpark-gguf:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Demo (CN / Global) · GitHub · Free API · Usage · DSpark · Skill

MiniCPM-OCR 1.0 DSpark — GGUF

GGUF build of the DSpark draft head for MiniCPM-OCR 1.0. A draft model, not a standalone OCR model — pair it with the matching main checkpoint.

Files

File	Size
`dspark-MiniCPM-OCR-1_0-F16.gguf`	0.606 GB
`dspark-MiniCPM-OCR-1_0-Q8_0.gguf`	0.327 GB
`dspark-MiniCPM-OCR-1_0-Q6_K.gguf`	0.255 GB
`dspark-MiniCPM-OCR-1_0-Q5_K_M.gguf`	0.233 GB
`dspark-MiniCPM-OCR-1_0-Q5_K_S.gguf`	0.232 GB
`dspark-MiniCPM-OCR-1_0-Q5_1.gguf`	0.243 GB
`dspark-MiniCPM-OCR-1_0-Q5_0.gguf`	0.232 GB
`dspark-MiniCPM-OCR-1_0-Q4_K_M.gguf`	0.211 GB
`dspark-MiniCPM-OCR-1_0-Q4_K_S.gguf`	0.209 GB
`dspark-MiniCPM-OCR-1_0-Q4_1.gguf`	0.220 GB
`dspark-MiniCPM-OCR-1_0-Q4_0.gguf`	0.209 GB

Use the main model's projector (mmproj-model-f16-4x.gguf from MiniCPM-OCR-1.0-gguf); this repository contains only the draft.

Usage

llama-cli \
  -m MiniCPM-OCR-1_0-Q8_0.gguf \
  --mmproj mmproj-model-f16-4x.gguf \
  -md dspark-MiniCPM-OCR-1_0-Q8_0.gguf \
  --spec-type draft-dspark \
  --image page.png -p "Text Recognition:" \
  --jinja -ngl 99 -ngld 99 -fa on

-md is the draft model and --spec-type draft-dspark enables the draft; -ngld offloads draft layers to GPU.

llama-mtmd-cli does not accept a draft model. Use llama-cli or llama-server when enabling DSpark with multimodal input.

Each tier carries the absolute target token IDs in its d2t tensor (the safetensors export stores them delta-encoded).

Related checkpoints

Format	Hugging Face	ModelScope
BF16 (original)	🤗	ModelScope
GGUF (llama.cpp)	🤗	ModelScope
AWQ W4A16	🤗	ModelScope
GPTQ W4A16	🤗	ModelScope
DSpark draft (BF16)	🤗	ModelScope
DSpark draft (GGUF) (this repo)	🤗	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: 3,668

GGUF

Model size

0.3B params

Architecture

dflash

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for openbmb/MiniCPM-OCR-1.0-DSpark-gguf

Base model

openbmb/MiniCPM-V-4.6

Finetuned

openbmb/MiniCPM-OCR-1.0

Finetuned

(5)

this model

Collection including openbmb/MiniCPM-OCR-1.0-DSpark-gguf

MiniCPM-OCR

Collection

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