Instructions to use vtava/functiongemma-270m-it-simple-tool-calling-memory-fusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vtava/functiongemma-270m-it-simple-tool-calling-memory-fusion with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vtava/functiongemma-270m-it-simple-tool-calling-memory-fusion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download functiongemma_memory_fusion.pt from vtava/functiongemma-270m-it-simple-tool-calling-memory-fusion: direct link, hf CLI and curl.
- Browser
- Download file 18.8 MB
-
https://huggingface.co/vtava/functiongemma-270m-it-simple-tool-calling-memory-fusion/resolve/main/functiongemma_memory_fusion.pt
- Command line
-
hf download hf://vtava/functiongemma-270m-it-simple-tool-calling-memory-fusion/functiongemma_memory_fusion.pt
-
curl -L -o functiongemma_memory_fusion.pt https://huggingface.co/vtava/functiongemma-270m-it-simple-tool-calling-memory-fusion/resolve/main/functiongemma_memory_fusion.pt
18.8 MB
- Xet hash:
- 47617019c46d078826174ae4e9dc08ff1dc246f46dfd6a2ef52ca173b00969aa
- Size of remote file:
- 18.8 MB
- SHA256:
- b0bc2ac4e5eacdf0da66aa1213f118bb151992c89dc120fbbc66e43b8aa15cb7
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