Instructions to use dimasik2987/2fe4a68a-315c-45ae-9563-f3a6bccca3cd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/2fe4a68a-315c-45ae-9563-f3a6bccca3cd 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, "dimasik2987/2fe4a68a-315c-45ae-9563-f3a6bccca3cd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9e319b1a78ff07db06415d00bc29394c05d01b2780c419a4c389b26f14814ed
- Size of remote file:
- 336 MB
- SHA256:
- c354e71c7f734aa6a3580e7a4fe8f653d131e42569b29e243d868ce9779a2817
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