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jtmuller
/
roadside-gemma-e2b

Text Generation
PEFT
Safetensors
English
gemma
gemma-4
lora
unsloth
litertlm
on-device
function-calling
tool-use
mobile
flutter
Model card Files Files and versions
xet
Community

Instructions to use jtmuller/roadside-gemma-e2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use jtmuller/roadside-gemma-e2b with PEFT:

    Task type is invalid.
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Unsloth Studio new

    How to use jtmuller/roadside-gemma-e2b 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 jtmuller/roadside-gemma-e2b 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 jtmuller/roadside-gemma-e2b to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for jtmuller/roadside-gemma-e2b to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="jtmuller/roadside-gemma-e2b",
        max_seq_length=2048,
    )
roadside-gemma-e2b / lora-adapter
1.03 GB
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  • 1 contributor
History: 1 commit
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jtmuller
Upload folder using huggingface_hub
e934e23 verified 1 day ago
  • adapter_config.json
    1.26 kB
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  • adapter_model.safetensors
    993 MB
    xet
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  • chat_template.jinja
    12 kB
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  • processor_config.json
    1.69 kB
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  • tokenizer.json
    32.2 MB
    xet
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  • tokenizer_config.json
    6.87 kB
    Upload folder using huggingface_hub 1 day ago