Instructions to use sergioalves/941ba499-8922-4a5c-b165-d32bf39f9d4a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sergioalves/941ba499-8922-4a5c-b165-d32bf39f9d4a 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, "sergioalves/941ba499-8922-4a5c-b165-d32bf39f9d4a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5628a09e1faf0a37dc9f34c9081d9a5440e27f97252605aefaf594693597ba59
- Size of remote file:
- 336 MB
- SHA256:
- 9e969a2a031ee4ea35485cd9778363e875d02f5f1e6534b198201512959e18b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.