Instructions to use dousery/functiongemma-mobile-actions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use dousery/functiongemma-mobile-actions 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 dousery/functiongemma-mobile-actions 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 dousery/functiongemma-mobile-actions to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for dousery/functiongemma-mobile-actions to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="dousery/functiongemma-mobile-actions", max_seq_length=2048, )
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## Model Details
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- **Base Model**: [google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it)
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- **Fine-tuning**: SFT with LoRA
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- **Dataset**: [google/mobile-actions](https://huggingface.co/datasets/google/mobile-actions)
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- **Params**: ~270M (base) + LoRA merged into final weights
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## Model Details
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- **Base Model**: [google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it)
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- **Fine-tuning**: SFT with LoRA
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- **Dataset**: [google/mobile-actions](https://huggingface.co/datasets/google/mobile-actions)
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- **Params**: ~270M (base) + LoRA merged into final weights
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