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:
- da318658e6b083335504c3a97e34ecd33763cae686ce9a20fed8f25a3e46408e
- Size of remote file:
- 6.78 kB
- SHA256:
- 7bb88382be8b4d113ecf18b00b71d36c06ab669e48e81578c3d5c992cc137d4b
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