Instructions to use shawhin/gemma-3-1b-tool-use with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shawhin/gemma-3-1b-tool-use with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shawhin/gemma-3-1b-tool-use", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shawhin/gemma-3-1b-tool-use: direct link, hf CLI and curl.
- Browser
- Download file 5.75 kB
-
https://huggingface.co/shawhin/gemma-3-1b-tool-use/resolve/a68c9c97da1ad9f340b5398e5825ebab8707ac71/training_args.bin
- Command line
-
hf download hf://shawhin/gemma-3-1b-tool-use@a68c9c97da1ad9f340b5398e5825ebab8707ac71/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shawhin/gemma-3-1b-tool-use/resolve/a68c9c97da1ad9f340b5398e5825ebab8707ac71/training_args.bin
5.75 kB
- Xet hash:
- 5fc89f8efd97a9ed07a204d22dac8f97f3c904e509013c369b59a279a43a95b1
- Size of remote file:
- 5.75 kB
- SHA256:
- ac139ed071484ebdc698444cba2a6854f61bb7577241b0f7fb29facaa3244dc2
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