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 tokenizer.json from mgbam/gemma-3: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/mgbam/gemma-3/resolve/main/tokenizer.json
- Command line
-
hf download hf://mgbam/gemma-3/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mgbam/gemma-3/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- f15ffe2cae485b12303f4bb84d0430052d7312428679e59d84f2074ae482d0e5
- Size of remote file:
- 33.4 MB
- SHA256:
- b6c35ee648c07754b44cd9e371c75d4caa05c4504910b7ad29b1847ee9d8ba5d
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