Instructions to use jnanliu/LiveMath-Judge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jnanliu/LiveMath-Judge with Transformers:

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

pipe = pipeline("text-generation", model="jnanliu/LiveMath-Judge")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("jnanliu/LiveMath-Judge")
model = AutoModel.from_pretrained("jnanliu/LiveMath-Judge", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jnanliu/LiveMath-Judge with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jnanliu/LiveMath-Judge"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jnanliu/LiveMath-Judge",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jnanliu/LiveMath-Judge

SGLang

How to use jnanliu/LiveMath-Judge 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 "jnanliu/LiveMath-Judge" \
    --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": "jnanliu/LiveMath-Judge",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "jnanliu/LiveMath-Judge" \
        --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": "jnanliu/LiveMath-Judge",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jnanliu/LiveMath-Judge with Docker Model Runner:
```
docker model run hf.co/jnanliu/LiveMath-Judge
```

jnanliu commited on Jan 10, 2025

Commit

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@@ -88,12 +88,12 @@ Following is the mG-Pass@16 results of Qwen2.5-72B-Instruct-as-Judge and LiveMat
 | Qwen2.5-Math-7B-Instruct | 37.91 | 39.54 |
 | Llama-3.1-8B-Instruct | 10.43 | 9.29 |
 | Llama-3.1-70B-Instruct | 21.37 | 22.12 |
-| Llama-3.3-70B-Instruct | 27.36 | 27.23 |
-| Mistral-Large-Instruct-2411 | 36.66 | 37.54 |
-| Qwen2.5-32B-Instruct | 39.09 | 39.44 |
-| Qwen2.5-72B-Instruct | 38.52 | 39.01 |
 | deepseek-math-7b-rl | 14.01 | 14.13 |
-| Qwen2.5-Math-72B-Instruct | 43.80 | 43.17 |
 ## Related Citation
 ```

 | Qwen2.5-Math-7B-Instruct | 37.91 | 39.54 |
 | Llama-3.1-8B-Instruct | 10.43 | 9.29 |
 | Llama-3.1-70B-Instruct | 21.37 | 22.12 |
+| Llama-3.3-70B-Instruct | 27.36 | 30.47 |
+| Mistral-Large-Instruct-2411 | 36.66 | 36.67 |
+| Qwen2.5-32B-Instruct | 39.09 | 37.84 |
+| Qwen2.5-72B-Instruct | 38.52 | 37.57 |
 | deepseek-math-7b-rl | 14.01 | 14.13 |
+| Qwen2.5-Math-72B-Instruct | 43.80 | 42.10 |
 ## Related Citation
 ```