Instructions to use internlm/AdvancedMathBench-AutoVerifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use internlm/AdvancedMathBench-AutoVerifier with Transformers:

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

pipe = pipeline("image-text-to-text", model="internlm/AdvancedMathBench-AutoVerifier")
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 AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("internlm/AdvancedMathBench-AutoVerifier")
model = AutoModelForMultimodalLM.from_pretrained("internlm/AdvancedMathBench-AutoVerifier", device_map="auto")
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?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use internlm/AdvancedMathBench-AutoVerifier with vLLM:

Install from pip and serve model

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

SGLang

How to use internlm/AdvancedMathBench-AutoVerifier 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 "internlm/AdvancedMathBench-AutoVerifier" \
    --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": "internlm/AdvancedMathBench-AutoVerifier",
		"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 "internlm/AdvancedMathBench-AutoVerifier" \
        --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": "internlm/AdvancedMathBench-AutoVerifier",
		"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 internlm/AdvancedMathBench-AutoVerifier with Docker Model Runner:
```
docker model run hf.co/internlm/AdvancedMathBench-AutoVerifier
```

debouter commited on 1 day ago

Commit

35e6bf1

verified ·

1 Parent(s): 2ad5873

Add project resource links and paper citation

Browse files

Files changed (1) hide show

README.md +23 -0

README.md CHANGED Viewed

@@ -11,6 +11,12 @@ tags:
 ---
 # AdvancedMathBench AutoVerifier
 AutoVerifier evaluates natural-language mathematical proofs, explains errors,
 and identifies the earliest incorrect step. It serves as the automatic grader
 for AdvancedMathBench's ProverBench.
@@ -74,3 +80,20 @@ AutoVerifier is a learned grader, not a formal proof checker, and can make error
 Tested package versions and validation scope are recorded in
 [compatibility.json](compatibility.json). License notices are provided in [LICENSE](LICENSE) and
 [NOTICE.md](NOTICE.md).

 ---
 # AdvancedMathBench AutoVerifier
+[Paper](https://arxiv.org/abs/2607.11849) ·
+[HF Paper](https://huggingface.co/papers/2607.11849) ·
+[GitHub](https://github.com/Debouter/AdvancedMathBench) ·
+[Dataset](https://huggingface.co/datasets/debouter/AdvancedMathBench) ·
+[AutoVerifier](https://huggingface.co/debouter/AdvancedMathBench-AutoVerifier)
 AutoVerifier evaluates natural-language mathematical proofs, explains errors,
 and identifies the earliest incorrect step. It serves as the automatic grader
 for AdvancedMathBench's ProverBench.
 Tested package versions and validation scope are recorded in
 [compatibility.json](compatibility.json). License notices are provided in [LICENSE](LICENSE) and
 [NOTICE.md](NOTICE.md).
+## Citation
+If you use AdvancedMathBench AutoVerifier in your research, please cite:
+```bibtex
+@misc{kong2026advancedmathbenchbenchmarksuiteadvanced,
+  title = {AdvancedMathBench: A Benchmark Suite for Advanced Mathematical Proof Generation and Verification},
+  author = {Lingkai Kong and Zijian Wu and Yuzhe Gu and Haiteng Zhao and Wenyong Huang and Shuang Sun and Zhicheng Xiong and Xiaotian Zhang and Shuya Zhao and Yan Wang and Disheng Xu and Wenwei Zhang and Kai Chen},
+  year = {2026},
+  eprint = {2607.11849},
+  archivePrefix = {arXiv},
+  primaryClass = {cs.CL},
+  doi = {10.48550/arXiv.2607.11849},
+  url = {https://arxiv.org/abs/2607.11849}
+}
+```