Instructions to use deepseek-ai/deepseek-coder-6.7b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepseek-ai/deepseek-coder-6.7b-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="deepseek-ai/deepseek-coder-6.7b-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base") model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use deepseek-ai/deepseek-coder-6.7b-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "deepseek-ai/deepseek-coder-6.7b-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepseek-ai/deepseek-coder-6.7b-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/deepseek-ai/deepseek-coder-6.7b-base
- SGLang
How to use deepseek-ai/deepseek-coder-6.7b-base 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-coder-6.7b-base" \ --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": "deepseek-ai/deepseek-coder-6.7b-base", "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 "deepseek-ai/deepseek-coder-6.7b-base" \ --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": "deepseek-ai/deepseek-coder-6.7b-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use deepseek-ai/deepseek-coder-6.7b-base with Docker Model Runner:
docker model run hf.co/deepseek-ai/deepseek-coder-6.7b-base
Download model-00002-of-00002.safetensors from deepseek-ai/deepseek-coder-6.7b-base: direct link, hf CLI and curl.
- Browser
- Download file 3.5 GB
-
https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base/resolve/main/model-00002-of-00002.safetensors
- Command line
-
hf download hf://deepseek-ai/deepseek-coder-6.7b-base/model-00002-of-00002.safetensors
-
curl -L -o model-00002-of-00002.safetensors https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base/resolve/main/model-00002-of-00002.safetensors
3.5 GB
- Xet hash:
- 47396653a919f2b045fa63c72a50e3b7eba0c19593c3d3fe4ef8716cd15b88ea
- Size of remote file:
- 3.5 GB
- SHA256:
- aca644afc72b8f4e86910c5bd130b32d5e21c92120a820b085e69b0a3a44ac53
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