Instructions to use nblinh/a5cc4cc4-6def-4537-a296-8698f571f813 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh/a5cc4cc4-6def-4537-a296-8698f571f813 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-135M") model = PeftModel.from_pretrained(base_model, "nblinh/a5cc4cc4-6def-4537-a296-8698f571f813") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 896f56555bfe5043e8d8b56e1ebcbc1dadb619942b8e2458bf39bd39ab540e79
- Size of remote file:
- 9.92 MB
- SHA256:
- 70b97b3c436ef5735469598292a7307711e3e98355cb4e591e86be3d3c415986
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