Instructions to use nhung01/2d72bed2-4a15-4f07-8dd1-86e991015d4d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/2d72bed2-4a15-4f07-8dd1-86e991015d4d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-360M") model = PeftModel.from_pretrained(base_model, "nhung01/2d72bed2-4a15-4f07-8dd1-86e991015d4d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df2b6d9bf1e0e4bd5abac77e962cda5a8a84b76c75ee261928be7f7e60ef4eb8
- Size of remote file:
- 17.5 MB
- SHA256:
- a8a1ab75de28a9009790ca3706080461961403babd12fffadda8ee8ed595fc7c
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