Instructions to use Coldbrew9/Fine_tuning_gemma_doubleQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Coldbrew9/Fine_tuning_gemma_doubleQ with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Coldbrew9/Fine_tuning_gemma_doubleQ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef9efc3a666e145aea70436abaaebcaa7c07cd2a16f088e6086ba23141cf5d60
- Size of remote file:
- 17.5 MB
- SHA256:
- cb7e592b7314175501c7fc56b904d581de569169ac90e5aa2ec11a860c2cbbaa
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