Instructions to use runfar/functiongemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use runfar/functiongemma with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("runfar/functiongemma", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use runfar/functiongemma 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 runfar/functiongemma 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 runfar/functiongemma to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for runfar/functiongemma to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="runfar/functiongemma", max_seq_length=2048, )
- Xet hash:
- 8e680bd23f3c40be652ca6c517ac0f59a29c97a3cc1c59d27203b306f162a1ad
- Size of remote file:
- 15.2 MB
- SHA256:
- 687f661409ee7b6bb1c5d5be43ad7872052079e185a92f8e20b21832a42f4cbe
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