Instructions to use dimasik87/76ef6c6c-3eaa-4c17-bf3c-448f7ef703e2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/76ef6c6c-3eaa-4c17-bf3c-448f7ef703e2 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, "dimasik87/76ef6c6c-3eaa-4c17-bf3c-448f7ef703e2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3425d76d1e125c2b5b7ed6d2ae2967e9bcdab52e82be8dfac1fa7392a98b781
- Size of remote file:
- 336 MB
- SHA256:
- a7a5166e92949007b029c93524142b4ed55679eb6e19276eec15b170dbadb74c
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