Instructions to use dimasik1987/5d83e8c6-09da-492f-8f79-6fb26fcd6aef with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik1987/5d83e8c6-09da-492f-8f79-6fb26fcd6aef with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "dimasik1987/5d83e8c6-09da-492f-8f79-6fb26fcd6aef") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94c738fea56cdafd7fe3832ace1f2b1ef890b64551ef422245947090691395c0
- Size of remote file:
- 336 MB
- SHA256:
- 0e1e22a7c24473ae2ce03415b098f515aeed520202a76c93116fabb734bf0b47
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