Instructions to use Cierra0506/MM-PRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Cierra0506/MM-PRM with Transformers:

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

pipe = pipeline("image-text-to-text", model="Cierra0506/MM-PRM", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Cierra0506/MM-PRM", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Cierra0506/MM-PRM with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Cierra0506/MM-PRM"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Cierra0506/MM-PRM",
		"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/Cierra0506/MM-PRM

SGLang

How to use Cierra0506/MM-PRM 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 "Cierra0506/MM-PRM" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Cierra0506/MM-PRM",
		"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 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 "Cierra0506/MM-PRM" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Cierra0506/MM-PRM",
		"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"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Cierra0506/MM-PRM with Docker Model Runner:
```
docker model run hf.co/Cierra0506/MM-PRM
```

MM-PRM: Enhancing Multimodal Mathematical Reasoning with Scalable Step-Level Supervision

[📂 GitHub] [📜 Paper]

Citation

If you find this project useful in your research, please consider citing:

@article{du2025mmprm,
      title={MM-PRM: Enhancing Multimodal Mathematical Reasoning with Scalable Step-Level Supervision},
      author={Lingxiao Du and Fanqing Meng and Zongkai Liu and Zhixiang Zhou and Ping Luo and Qiaosheng Zhang and Wenqi Shao},
      year={2025},
      journal={arXiv preprint arXiv:2505.13427},
}

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Safetensors

Model size

8B params

Tensor type

BF16

Model tree for Cierra0506/MM-PRM

Base model

OpenGVLab/InternVL2_5-8B

Finetuned

(16)

this model

Dataset used to train Cierra0506/MM-PRM

Paper for Cierra0506/MM-PRM

MM-PRM: Enhancing Multimodal Mathematical Reasoning with Scalable Step-Level Supervision

Paper • 2505.13427 • Published May 19, 2025 • 26