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RANDMEDIATION
/
DiogenialRAG

Text Generation
MLX
French
Greek
mistral-7b
Ancient greek
Model card Files Files and versions
xet
Community

Instructions to use RANDMEDIATION/DiogenialRAG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use RANDMEDIATION/DiogenialRAG with MLX:

    # Make sure mlx-lm is installed
    # pip install --upgrade mlx-lm
    # if on a CUDA device, also pip install mlx[cuda]
    
    # Generate text with mlx-lm
    from mlx_lm import load, generate
    
    model, tokenizer = load("RANDMEDIATION/DiogenialRAG")
    
    prompt = "Once upon a time in"
    text = generate(model, tokenizer, prompt=prompt, verbose=True)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • LM Studio
  • MLX LM

    How to use RANDMEDIATION/DiogenialRAG with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Generate some text
    mlx_lm.generate --model "RANDMEDIATION/DiogenialRAG" --prompt "Once upon a time"
DiogenialRAG
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  • 2 contributors
History: 17 commits
Luc18's picture
Luc18
Update README.md
c92ff8b verified about 2 years ago
  • .gitattributes
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  • README.md
    2.48 kB
    Update README.md about 2 years ago
  • config.json
    616 Bytes
    xet
    k about 2 years ago
  • special_tokens_map.json
    414 Bytes
    xet
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  • tokenizer.json
    1.8 MB
    xet
    First about 2 years ago
  • tokenizer.model
    493 kB
    xet
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  • tokenizer_config.json
    967 Bytes
    xet
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  • weights.00.safetensors
    14.5 GB
    xet
    First about 2 years ago