Instructions to use dimasik87/302a7ffc-f8b1-49ea-85e2-22e350a994de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/302a7ffc-f8b1-49ea-85e2-22e350a994de with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("samoline/0243b90c-8e39-4616-a4c6-82e4ad8a78c6") model = PeftModel.from_pretrained(base_model, "dimasik87/302a7ffc-f8b1-49ea-85e2-22e350a994de") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d3ae6a3ac74bae6426398f971529f6ab97e56764f258139174c52b2480ec984
- Size of remote file:
- 97.4 MB
- SHA256:
- 970cc77c4e1a0a56a0155866450c632c728c5b3a3b36b92a89156544e3a75a53
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