Instructions to use Intel/DeepSeek-V4-Flash-W4A16-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/DeepSeek-V4-Flash-W4A16-AutoRound with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Intel/DeepSeek-V4-Flash-W4A16-AutoRound")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Intel/DeepSeek-V4-Flash-W4A16-AutoRound") model = AutoModelForCausalLM.from_pretrained("Intel/DeepSeek-V4-Flash-W4A16-AutoRound", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Intel/DeepSeek-V4-Flash-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-Flash-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-Flash-W4A16-AutoRound", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Intel/DeepSeek-V4-Flash-W4A16-AutoRound
- SGLang
How to use Intel/DeepSeek-V4-Flash-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-Flash-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-Flash-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-Flash-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-Flash-W4A16-AutoRound", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Intel/DeepSeek-V4-Flash-W4A16-AutoRound with Docker Model Runner:
docker model run hf.co/Intel/DeepSeek-V4-Flash-W4A16-AutoRound
Download DeepSeek_V4.pdf from Intel/DeepSeek-V4-Flash-W4A16-AutoRound: direct link, hf CLI and curl.
- Browser
- Download file 4.48 MB
-
https://huggingface.co/Intel/DeepSeek-V4-Flash-W4A16-AutoRound/resolve/main/DeepSeek_V4.pdf
- Command line
-
hf download hf://Intel/DeepSeek-V4-Flash-W4A16-AutoRound/DeepSeek_V4.pdf
-
curl -L -o DeepSeek_V4.pdf https://huggingface.co/Intel/DeepSeek-V4-Flash-W4A16-AutoRound/resolve/main/DeepSeek_V4.pdf
4.48 MB
- Xet hash:
- 60ba3f8de5d5172b5f3230b024eff941ac2ca747c301035124a2787e6169be2b
- Size of remote file:
- 4.48 MB
- SHA256:
- 8a03dadae71894de1515da33e296f0df1dbeed3e7f4bf0badd087f9af77f29e9
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