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mattPearce
/
wp-plugin-recommender-mlx

Text Generation
MLX
English
qwen2
conversational
4-bit precision
Model card Files Files and versions
xet
Community

Instructions to use mattPearce/wp-plugin-recommender-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use mattPearce/wp-plugin-recommender-mlx 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("mattPearce/wp-plugin-recommender-mlx")
    
    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 Settings
  • LM Studio
  • Pi

    How to use mattPearce/wp-plugin-recommender-mlx with Pi:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "mattPearce/wp-plugin-recommender-mlx"
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "mlx-lm": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "mattPearce/wp-plugin-recommender-mlx"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Hermes Agent new

    How to use mattPearce/wp-plugin-recommender-mlx with Hermes Agent:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "mattPearce/wp-plugin-recommender-mlx"
    Configure Hermes
    # Install Hermes:
    curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
    hermes setup
    # Point Hermes at the local server:
    hermes config set model.provider custom
    hermes config set model.base_url http://127.0.0.1:8080/v1
    hermes config set model.default mattPearce/wp-plugin-recommender-mlx
    Run Hermes
    hermes
  • MLX LM

    How to use mattPearce/wp-plugin-recommender-mlx with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Interactive chat REPL
    mlx_lm.chat --model "mattPearce/wp-plugin-recommender-mlx"
    Run an OpenAI-compatible server
    # Install MLX LM
    uv tool install mlx-lm
    # Start the server
    mlx_lm.server --model "mattPearce/wp-plugin-recommender-mlx"
    # Calling the OpenAI-compatible server with curl
    curl -X POST "http://localhost:8000/v1/chat/completions" \
       -H "Content-Type: application/json" \
       --data '{
         "model": "mattPearce/wp-plugin-recommender-mlx",
         "messages": [
           {"role": "user", "content": "Hello"}
         ]
       }'
wp-plugin-recommender-mlx
11.4 MB
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  • 1 contributor
History: 9 commits
mattPearce's picture
mattPearce
Add chat_template.jinja
422763a verified 4 months ago
  • .gitattributes
    1.57 kB
    Upload tokenizer.json with huggingface_hub 4 months ago
  • README.md
    559 Bytes
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  • added_tokens.json
    605 Bytes
    Upload added_tokens.json with huggingface_hub 4 months ago
  • chat_template.jinja
    2.51 kB
    Add chat_template.jinja 4 months ago
  • config.json
    1.58 kB
    Upload config.json with huggingface_hub 4 months ago
  • generation_config.json
    242 Bytes
    Upload generation_config.json with huggingface_hub 4 months ago
  • special_tokens_map.json
    613 Bytes
    Upload special_tokens_map.json with huggingface_hub 4 months ago
  • tokenizer.json
    11.4 MB
    xet
    Upload tokenizer.json with huggingface_hub 4 months ago
  • tokenizer_config.json
    4.69 kB
    Upload tokenizer_config.json with huggingface_hub 4 months ago