Instructions to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="second-state/Deepseek-Coder-6.7B-Instruct-GGUF")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("second-state/Deepseek-Coder-6.7B-Instruct-GGUF") model = AutoModelForCausalLM.from_pretrained("second-state/Deepseek-Coder-6.7B-Instruct-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "second-state/Deepseek-Coder-6.7B-Instruct-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "second-state/Deepseek-Coder-6.7B-Instruct-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
- SGLang
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF 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 "second-state/Deepseek-Coder-6.7B-Instruct-GGUF" \ --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": "second-state/Deepseek-Coder-6.7B-Instruct-GGUF", "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 "second-state/Deepseek-Coder-6.7B-Instruct-GGUF" \ --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": "second-state/Deepseek-Coder-6.7B-Instruct-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Ollama:
ollama run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
- Lemonade
How to use second-state/Deepseek-Coder-6.7B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull second-state/Deepseek-Coder-6.7B-Instruct-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Deepseek-Coder-6.7B-Instruct-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Xin Liu commited on
Commit ·
cc85b1c
1
Parent(s): 90e968a
Add `deepseek-coder-6.7b-instruct.Q5_K_M.gguf`
Browse filesSigned-off-by: Xin Liu <sam@secondstate.io>
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# Deepseek-Coder-6.7B-Instruct
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## Prompt Template
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```text
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You are an AI programming assistant, utilizing the DeepSeek Coder model, developed by DeepSeek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer.
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### Instruction:
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{question_1}
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### Response:
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{answer_1}
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<|EOT|>
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### Instruction:
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{question_2}
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### Response:
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```
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