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.model from mgbam/gemma-3: direct link, hf CLI and curl.
- Browser
- Download file 4.7 MB
-
https://huggingface.co/mgbam/gemma-3/resolve/main/tokenizer.model
- Command line
-
hf download hf://mgbam/gemma-3/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/mgbam/gemma-3/resolve/main/tokenizer.model
4.7 MB
- Xet hash:
- 91480cfef423b04be801a5da51542180dee38280681cfa1fcd28a32de5094814
- Size of remote file:
- 4.7 MB
- SHA256:
- ea5f0cc48abfbfc04d14562270a32e02149a3e7035f368cc5a462786f4a59961
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