Instructions to use dzanbek/c3cd6cc4-740b-4f58-a3f1-1087bed0bf4d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/c3cd6cc4-740b-4f58-a3f1-1087bed0bf4d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "dzanbek/c3cd6cc4-740b-4f58-a3f1-1087bed0bf4d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90436db668c9bad07297d18f6317ffa7d876789ec35f67ddcdbcc9f5bd42853f
- Size of remote file:
- 6.78 kB
- SHA256:
- be4cd95af4f17ef2221513c65c67c1af76128cff1d381af58fb678e461967c2b
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