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

Libraries

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

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/DeepSeek-V2", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-V2", trust_remote_code=True, 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 deepseek-ai/DeepSeek-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-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-V2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

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

SGLang

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

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

luofuli commited on May 6, 2024

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@@ -110,12 +110,12 @@ Evaluation results on the ``Needle In A Haystack`` (NIAH) tests.  DeepSeek-V2 pe
 | Benchmark | Domain         | QWen1.5 72B Chat | Mixtral 8x22B | LLaMA3 70B Instruct | DeepSeek V1 Chat (SFT) | DeepSeek V2 Chat(SFT) | DeepSeek V2 Chat(RL) |
 |:-----------:|:----------------:|:------------------:|:---------------:|:---------------------:|:-------------:|:-----------------------:|:----------------------:|
 | **MMLU**      | English        | 76.2             | 77.8          | 80.3                | 71.1        | 78.4                 | 77.8                 |
-| **BBH**       | English        | 65.9             | 78.4          | 78.4                | 71.7        | 81.3                 | 79.7                 |
 | **C-Eval**    | Chinese        | 82.2             | 60.0          | 67.9                | 65.2        | 80.9                 | 78.0                 |
 | **CMMLU**     | Chinese        | 82.9             | 61.0          | 70.7                | 67.8        | 82.4                 | 81.6                 |
 | **HumanEval** | Code           | 68.9             | 75.0          | 76.2                | 73.8        | 76.8                 | 81.1                 |
-| **MBPP**      | Code           | 43.4             | 64.4          | 69.8                | 61.4        | 70.4                 | 72.0                 |
-|   **LiveCodeBench  (1201-0401)**     | Code           | 18.5             | 24.0          | 32.3                | 19.0        | 28.7                 | 31.3                 |
 | **GSM8K**     | Math           | 81.9             | 87.9          | 93.2                | 84.1        | 90.8                 | 92.2                 |
 | **Math**      | Math           | 40.6             | 49.8          | 48.5                | 32.6        | 52.7                 | 53.9                 |

 | Benchmark | Domain         | QWen1.5 72B Chat | Mixtral 8x22B | LLaMA3 70B Instruct | DeepSeek V1 Chat (SFT) | DeepSeek V2 Chat(SFT) | DeepSeek V2 Chat(RL) |
 |:-----------:|:----------------:|:------------------:|:---------------:|:---------------------:|:-------------:|:-----------------------:|:----------------------:|
 | **MMLU**      | English        | 76.2             | 77.8          | 80.3                | 71.1        | 78.4                 | 77.8                 |
+| **BBH**       | English        | 65.9             | 78.4          | 80.1                | 71.7        | 81.3                 | 79.7                 |
 | **C-Eval**    | Chinese        | 82.2             | 60.0          | 67.9                | 65.2        | 80.9                 | 78.0                 |
 | **CMMLU**     | Chinese        | 82.9             | 61.0          | 70.7                | 67.8        | 82.4                 | 81.6                 |
 | **HumanEval** | Code           | 68.9             | 75.0          | 76.2                | 73.8        | 76.8                 | 81.1                 |
+| **MBPP**      | Code           | 52.2             | 64.4          | 69.8                | 61.4        | 70.4                 | 72.0                 |
+|   **LiveCodeBench  (0901-0401)**     | Code           | 18.8             | 25.0          | 30.5                | 18.3        | 28.7                 | 32.5                 |
 | **GSM8K**     | Math           | 81.9             | 87.9          | 93.2                | 84.1        | 90.8                 | 92.2                 |
 | **Math**      | Math           | 40.6             | 49.8          | 48.5                | 32.6        | 52.7                 | 53.9                 |