Instructions to use np28work/npre_gemma_glaive_function_calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use np28work/npre_gemma_glaive_function_calling with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("np28work/npre_gemma_glaive_function_calling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use np28work/npre_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 np28work/npre_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 np28work/npre_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 np28work/npre_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="np28work/npre_gemma_glaive_function_calling", max_seq_length=2048, )
- Xet hash:
- 24c293f00a1fd364ca1e679c85a088e60a7fff4e8f5d99f319320249a3a20bed
- Size of remote file:
- 78.5 MB
- SHA256:
- aae895100f8b8f5e26a1df4168f9b32aed11d7f658b9464a036183b0fc3a2597
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