Instructions to use deepseek-ai/DeepSeek-Math-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use deepseek-ai/DeepSeek-Math-V2 with Transformers:

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

pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-Math-V2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-Math-V2", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use deepseek-ai/DeepSeek-Math-V2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "deepseek-ai/DeepSeek-Math-V2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "deepseek-ai/DeepSeek-Math-V2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/deepseek-ai/DeepSeek-Math-V2

SGLang

How to use deepseek-ai/DeepSeek-Math-V2 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 "deepseek-ai/DeepSeek-Math-V2" \
    --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": "deepseek-ai/DeepSeek-Math-V2",
		"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 "deepseek-ai/DeepSeek-Math-V2" \
        --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": "deepseek-ai/DeepSeek-Math-V2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use deepseek-ai/DeepSeek-Math-V2 with Docker Model Runner:
```
docker model run hf.co/deepseek-ai/DeepSeek-Math-V2
```

ZhihongShao commited on Nov 27, 2025

Commit

6ea7c60

1 Parent(s): 9b04ba2

update README.md

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -58,7 +58,7 @@ Below are evaluation results on [IMO-ProofBench](https://github.com/google-deepm
 **IMO-ProofBench**
 <p align="center">
-  <img width="100%" src="https://github.com/deepseek-ai/DeepSeek-Math-V2/tree/main/figures/IMO-ProofBench.png?raw=true">
 </p>
@@ -67,7 +67,7 @@ Below are evaluation results on [IMO-ProofBench](https://github.com/google-deepm
 **Mathematics Competitions**
 <p align="center">
-  <img width=41%" src="https://github.com/deepseek-ai/DeepSeek-Math-V2/tree/main/figures/Competitions.png?raw=true">
 </p>
 ## 4. Quick Start

 **IMO-ProofBench**
 <p align="center">
+  <img width="100%" src="https://raw.githubusercontent.com/deepseek-ai/DeepSeek-Math-V2/refs/heads/main/figures/IMO-ProofBench.png">
 </p>
 **Mathematics Competitions**
 <p align="center">
+  <img width=41%" src="https://raw.githubusercontent.com/deepseek-ai/DeepSeek-Math-V2/refs/heads/main/figures/Competitions.png">
 </p>
 ## 4. Quick Start