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N8Programs
/
talkie-box

Text Generation
MLX
Safetensors
English
conversational
Model card Files Files and versions
xet
Community

Instructions to use N8Programs/talkie-box with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use N8Programs/talkie-box 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("N8Programs/talkie-box")
    
    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 N8Programs/talkie-box with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Interactive chat REPL
    mlx_lm.chat --model "N8Programs/talkie-box"
    Run an OpenAI-compatible server
    # Install MLX LM
    uv tool install mlx-lm
    # Start the server
    mlx_lm.server --model "N8Programs/talkie-box"
    # Calling the OpenAI-compatible server with curl
    curl -X POST "http://localhost:8000/v1/chat/completions" \
       -H "Content-Type: application/json" \
       --data '{
         "model": "N8Programs/talkie-box",
         "messages": [
           {"role": "user", "content": "Hello"}
         ]
       }'
talkie-box
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  • 1 contributor
History: 8 commits
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N8Programs
Update README.md
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  • talkie_mlx.py
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  • tokenizer.json
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  • tokenizer_config.json
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