Instructions to use bane5631/b16d3ae9-0778-4227-8847-a52a0826b669 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/b16d3ae9-0778-4227-8847-a52a0826b669 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, "bane5631/b16d3ae9-0778-4227-8847-a52a0826b669") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0463b742a44e0189fbfb570c76c7ed586bccbf804512dad36d307cd507697202
- Size of remote file:
- 83.9 MB
- SHA256:
- 7379ba764479301e551ae4d8ad7a2d6840a1efe4147b0c6ce1d1aada12ac1530
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.