Instructions to use thangla01/70e31d4e-2c6c-4d94-a9c6-56a0af123b68 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/70e31d4e-2c6c-4d94-a9c6-56a0af123b68 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4") model = PeftModel.from_pretrained(base_model, "thangla01/70e31d4e-2c6c-4d94-a9c6-56a0af123b68") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f43ec29e32146c39deacfe57235e8cd1133442e05641d5a1d974289ccb835d5
- Size of remote file:
- 6.78 kB
- SHA256:
- a15672cba9cb9c090d40cf002c39a4fbe32f59c592cad1e67c94dfb9f4c6aec2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.