Instructions to use Intel/DeepSeek-V4-Pro-W4A16-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/DeepSeek-V4-Pro-W4A16-AutoRound with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Intel/DeepSeek-V4-Pro-W4A16-AutoRound")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Intel/DeepSeek-V4-Pro-W4A16-AutoRound") model = AutoModelForCausalLM.from_pretrained("Intel/DeepSeek-V4-Pro-W4A16-AutoRound") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Intel/DeepSeek-V4-Pro-W4A16-AutoRound with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Intel/DeepSeek-V4-Pro-W4A16-AutoRound" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Intel/DeepSeek-V4-Pro-W4A16-AutoRound", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Intel/DeepSeek-V4-Pro-W4A16-AutoRound
- SGLang
How to use Intel/DeepSeek-V4-Pro-W4A16-AutoRound 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 "Intel/DeepSeek-V4-Pro-W4A16-AutoRound" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Intel/DeepSeek-V4-Pro-W4A16-AutoRound", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Intel/DeepSeek-V4-Pro-W4A16-AutoRound" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Intel/DeepSeek-V4-Pro-W4A16-AutoRound", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Intel/DeepSeek-V4-Pro-W4A16-AutoRound with Docker Model Runner:
docker model run hf.co/Intel/DeepSeek-V4-Pro-W4A16-AutoRound
File size: 2,748 Bytes
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"tools": [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the weather for a specific location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city name"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": "Temperature unit"
}
},
"required": ["location"]
}
}
},
{
"type": "function",
"function": {
"name": "search",
"description": "Search the web for information",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query"
},
"num_results": {
"type": "integer",
"description": "Number of results to return"
}
},
"required": ["query"]
}
}
}
],
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "What's the weather in Beijing?"
},
{
"role": "assistant",
"reasoning_content": "The user wants to know the weather in Beijing. I should use the get_weather tool.",
"tool_calls": [
{
"id": "call_001",
"type": "function",
"function": {
"name": "get_weather",
"arguments": "{\"location\": \"Beijing\", \"unit\": \"celsius\"}"
}
}
]
},
{
"role": "tool",
"tool_call_id": "call_001",
"content": "{\"temperature\": 22, \"condition\": \"sunny\", \"humidity\": 45}"
},
{
"role": "assistant",
"reasoning_content": "Got the weather data. Let me format a nice response.",
"content": "The weather in Beijing is currently sunny with a temperature of 22°C and 45% humidity."
}
]
}
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