Instructions to use mgbam/gemma-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgbam/gemma-3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mgbam/gemma-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from mgbam/gemma-3: direct link, hf CLI and curl.
- Browser
- Download file 76.9 MB
-
https://huggingface.co/mgbam/gemma-3/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://mgbam/gemma-3/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/mgbam/gemma-3/resolve/main/adapter_model.safetensors
76.9 MB
- Xet hash:
- c759945b340eb2b1af03fe01f3fe9ebbb6d498c75da2a12a3d3394278106343d
- Size of remote file:
- 76.9 MB
- SHA256:
- 167033830501d0107ea7436917610bc61ac49b81dfc9eb10ef1ead311fb5dc2a
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