Instructions to use dimasik1987/bbb2e770-4720-449e-b95f-480b14848330 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik1987/bbb2e770-4720-449e-b95f-480b14848330 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-360M") model = PeftModel.from_pretrained(base_model, "dimasik1987/bbb2e770-4720-449e-b95f-480b14848330") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e66b36f8ced175fab3861c3041c14ad4d08798835468626a25f3d0c7a7fb16e
- Size of remote file:
- 34.8 MB
- SHA256:
- 3416587368ae900f9e1535ad6637112c22cb67378db7b355d8301c8502d97197
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