Instructions to use Gabriel/diffu-minicpm-ocr-htr-dspark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Gabriel/diffu-minicpm-ocr-htr-dspark with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Gabriel/diffu-minicpm-ocr-htr-dspark", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Gabriel/diffu-minicpm-ocr-htr-dspark", trust_remote_code=True, device_map="auto")

MiniCPM-OCR

How to use Gabriel/diffu-minicpm-ocr-htr-dspark with MiniCPM-OCR:

pip install "minicpm-ocr[all]" huggingface_hub

# Deploy Gabriel/diffu-minicpm-ocr-htr-dspark as a recognition service before running the Python example:
# https://github.com/OpenBMB/MiniCPM-OCR/blob/main/docs/vllm_deploy_en.md
# vLLM: load the model above; use --port 8080,
# --served-model-name minicpm-ocr and --max-model-len 40960.
# Layout detection uses cuda:0; recognition runs on the deployed service.

from importlib.resources import files
from pathlib import Path

from minicpmvocr import load_config, pipelined_run
from huggingface_hub import snapshot_download

layout_model = snapshot_download("PaddlePaddle/PP-DocLayoutV3")
cfg = load_config(
    str(files("minicpmvocr").joinpath("configs/minicpmvocr.yaml")),
    overrides={
        "input": {"file_path": str(Path("demo.png").resolve())},
        "engine": {
            "type": "vllm",
            "server_url": "http://127.0.0.1:8080",
            "model_name": "minicpm-ocr",
            "max_model_len": 40960,
        },
        "layout": {"model_dir": layout_model, "device": "cuda:0"},
        # Render PDFs in-process so this example also works without a main guard.
        "pipeline": {"overlap_layout": True, "render_workers": 1},
    },
)
pipelined_run(cfg)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Gabriel/diffu-minicpm-ocr-htr-dspark with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Gabriel/diffu-minicpm-ocr-htr-dspark

SGLang

How to use Gabriel/diffu-minicpm-ocr-htr-dspark with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Gabriel/diffu-minicpm-ocr-htr-dspark" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Gabriel/diffu-minicpm-ocr-htr-dspark",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Gabriel/diffu-minicpm-ocr-htr-dspark" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Gabriel/diffu-minicpm-ocr-htr-dspark",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Gabriel/diffu-minicpm-ocr-htr-dspark with Docker Model Runner:
```
docker model run hf.co/Gabriel/diffu-minicpm-ocr-htr-dspark
```

Gabriel commited on 6 days ago

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