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Jabr7
/
Mini-Boni

Transformers
Safetensors
Spanish
unsloth
lora
gemma
whatsapp
Model card Files Files and versions
xet
Community

Instructions to use Jabr7/Mini-Boni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Jabr7/Mini-Boni with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Jabr7/Mini-Boni", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Unsloth Studio new

    How to use Jabr7/Mini-Boni with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for Jabr7/Mini-Boni to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for Jabr7/Mini-Boni to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for Jabr7/Mini-Boni to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="Jabr7/Mini-Boni",
        max_seq_length=2048,
    )
Mini-Boni
45.1 MB
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  • 1 contributor
History: 5 commits
Jabr7's picture
Jabr7
Update README.md
723bf6e verified 8 months ago
  • .gitattributes
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  • README.md
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  • adapter_config.json
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  • adapter_model.safetensors
    6.4 MB
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  • chat_template.jinja
    591 Bytes
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  • special_tokens_map.json
    636 Bytes
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  • tokenizer.json
    34.4 MB
    xet
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  • tokenizer.model
    4.24 MB
    xet
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  • tokenizer_config.json
    46.4 kB
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