Instructions to use dimasik1987/fffe9252-2f0a-41e0-9f1b-12c5798388e4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik1987/fffe9252-2f0a-41e0-9f1b-12c5798388e4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "dimasik1987/fffe9252-2f0a-41e0-9f1b-12c5798388e4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 865f1345288f6b4193c7fa649b3c4e7b633766e4c9afdeb10f45dbad67e9692e
- Size of remote file:
- 336 MB
- SHA256:
- 259f9e2ebaaab59147a26dee53c2860c8904385e8d5220680087c5e28db054cc
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