Instructions to use chirbard/gemma_3_ft_unsloth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chirbard/gemma_3_ft_unsloth with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chirbard/gemma_3_ft_unsloth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from chirbard/gemma_3_ft_unsloth: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/chirbard/gemma_3_ft_unsloth/resolve/main/tokenizer.json
- Command line
-
hf download hf://chirbard/gemma_3_ft_unsloth/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/chirbard/gemma_3_ft_unsloth/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- 9c18d4d82f809dfa4a6ad816a374152465cf5b08ae49a49fda849cb0f9e39482
- Size of remote file:
- 33.4 MB
- SHA256:
- a8847cd115f5a1be8d9ffd7603af7de05c75f3d9f17e98d0e033a0d1f2587e3f
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