Instructions to use nhung03/f1e79c93-e75d-4c15-bdb6-da57e4b209ae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/f1e79c93-e75d-4c15-bdb6-da57e4b209ae with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Maykeye/TinyLLama-v0") model = PeftModel.from_pretrained(base_model, "nhung03/f1e79c93-e75d-4c15-bdb6-da57e4b209ae") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 333770035fc84516afffa579519f344fb277d68b97abb11fc7ff7c39d661e2de
- Size of remote file:
- 6.78 kB
- SHA256:
- ee0543d67df9f06c9242b9f25bd01cbdaa67bdf199c00e3b2f5b458ce406aa7a
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