Instructions to use Vasanth/unsloth-gemma-glaive-function-calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vasanth/unsloth-gemma-glaive-function-calling with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Vasanth/unsloth-gemma-glaive-function-calling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Vasanth/unsloth-gemma-glaive-function-calling 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 Vasanth/unsloth-gemma-glaive-function-calling 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 Vasanth/unsloth-gemma-glaive-function-calling to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Vasanth/unsloth-gemma-glaive-function-calling to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Vasanth/unsloth-gemma-glaive-function-calling", max_seq_length=2048, )
- Xet hash:
- 12c3e478b295a359ca16be2ba59b3c77df5b4207988154344d37b407e3cf7924
- Size of remote file:
- 4.24 MB
- SHA256:
- 5ff84841ba0d37cea281b9cf0a5a46054ffd4181fb1be09ccc69cf9ccb419325
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