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smarttasks
/
DeepSeek-R1-Distill-Qwen-7B-GGUF

Text Generation
GGUF
English
quantized
llama.cpp
scorecard
governance
validated
local-llm
on-device
agentic
tool-calling
function-calling
agents
ai-agents
rag
q4_k_m
q8_0
conversational
Model card Files Files and versions
xet
Community

Instructions to use smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use smarttasks/DeepSeek-R1-Distill-Qwen-7B-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 smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf smarttasks/DeepSeek-R1-Distill-Qwen-7B-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 smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf smarttasks/DeepSeek-R1-Distill-Qwen-7B-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 smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama cli -hf smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
    Use Docker
    docker model run hf.co/smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
  • Llama new
  • LM Studio
  • Jan
  • vLLM

    How to use smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "smarttasks/DeepSeek-R1-Distill-Qwen-7B-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": "smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
  • Ollama

    How to use smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF with Ollama:

    ollama run hf.co/smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
  • Unsloth Desktop
  • Docker Model Runner

    How to use smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF with Docker Model Runner:

    docker model run hf.co/smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
  • Lemonade

    How to use smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull smarttasks/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
    Run and chat with the model
    lemonade run user.DeepSeek-R1-Distill-Qwen-7B-GGUF-Q4_K_M
    List all available models
    lemonade list
  • Atomic Chat
DeepSeek-R1-Distill-Qwen-7B-GGUF
28.3 GB
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  • 1 contributor
History: 2 commits
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roenb
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  • .gitattributes
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  • DeepSeek-R1-Distill-Qwen-7B-Q3_K_M.gguf
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  • DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf
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  • DeepSeek-R1-Distill-Qwen-7B-Q6_K.gguf
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  • DeepSeek-R1-Distill-Qwen-7B-Q8_0.gguf
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  • MANIFEST.json
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  • README.md
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  • SECURITY.md
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  • SHA256SUMS
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  • scorecard.json
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