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mlx-community
/
DeepSeek-V4-Pro-8bit

Text Generation
MLX
Safetensors
English
deepseek_v4
conversational
8-bit precision
Model card Files Files and versions
xet
Community
1

Instructions to use mlx-community/DeepSeek-V4-Pro-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use mlx-community/DeepSeek-V4-Pro-8bit with MLX:

    # Make sure mlx-lm is installed
    # pip install --upgrade mlx-lm
    
    # Generate text with mlx-lm
    from mlx_lm import load, generate
    
    model, tokenizer = load("mlx-community/DeepSeek-V4-Pro-8bit")
    
    prompt = "Write a story about Einstein"
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )
    
    text = generate(model, tokenizer, prompt=prompt, verbose=True)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • LM Studio
  • MLX LM

    How to use mlx-community/DeepSeek-V4-Pro-8bit with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Interactive chat REPL
    mlx_lm.chat --model "mlx-community/DeepSeek-V4-Pro-8bit"
    Run an OpenAI-compatible server
    # Install MLX LM
    uv tool install mlx-lm
    # Start the server
    mlx_lm.server --model "mlx-community/DeepSeek-V4-Pro-8bit"
    # Calling the OpenAI-compatible server with curl
    curl -X POST "http://localhost:8000/v1/chat/completions" \
       -H "Content-Type: application/json" \
       --data '{
         "model": "mlx-community/DeepSeek-V4-Pro-8bit",
         "messages": [
           {"role": "user", "content": "Hello"}
         ]
       }'
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Is this file size 247 GB correct for 8 bit, while 4-bit version has 837 GB?

1
#1 opened 10 days ago by
Seth-TW
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