Instructions to use Rcarvalo/cesame4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rcarvalo/cesame4bit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Rcarvalo/cesame4bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Commit History
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Training step 453 - epoch 3 - loss 4.9884 (Trained with Unsloth)
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Training step 302 - epoch 2 - loss 5.113 (Trained with Unsloth)
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Training step 151 - epoch 1 - loss 5.4184 (Trained with Unsloth)
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initial commit
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