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aavhawkeye
/
privacy-gateway-adapter

Text Generation
PEFT
Safetensors
English
lora
cybersecurity
privacy
redaction
unsloth
conversational
Model card Files Files and versions
xet
Community

Instructions to use aavhawkeye/privacy-gateway-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use aavhawkeye/privacy-gateway-adapter with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/gpt-oss-20b-bnb-4bit")
    model = PeftModel.from_pretrained(base_model, "aavhawkeye/privacy-gateway-adapter")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Unsloth Studio new

    How to use aavhawkeye/privacy-gateway-adapter 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 aavhawkeye/privacy-gateway-adapter 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 aavhawkeye/privacy-gateway-adapter to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for aavhawkeye/privacy-gateway-adapter to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="aavhawkeye/privacy-gateway-adapter",
        max_seq_length=2048,
    )

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  • .gitattributes
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  • README.md
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  • adapter_config.json
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  • tokenizer.json
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  • tokenizer_config.json
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