Instructions to use laquythang/3b42de14-40f8-4788-95e3-d9ee17cff65a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use laquythang/3b42de14-40f8-4788-95e3-d9ee17cff65a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Mistral-Nemo-Instruct-2407") model = PeftModel.from_pretrained(base_model, "laquythang/3b42de14-40f8-4788-95e3-d9ee17cff65a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 599289162a13adc11db2d332cf5b09e98c6a49b639116a9acdf1b1539ac66e74
- Size of remote file:
- 114 MB
- SHA256:
- f746aa308d2bc80e24dee4c8d15dacddc7d6e5d62be516bdb84f227a159ee4c2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.