Instructions to use havinash-ai/ea44769e-31b2-40b0-a015-89790aecfafe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/ea44769e-31b2-40b0-a015-89790aecfafe 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, "havinash-ai/ea44769e-31b2-40b0-a015-89790aecfafe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08681d03135aa365cb0cba9971c4ac5f967f1be1de42354fbdd29f55abca1a0f
- Size of remote file:
- 336 MB
- SHA256:
- d862b6dab833b4dd9a6271a630ec2d41b0eaebd7264b6da7e470d4ac6cf49c36
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.