Instructions to use laquythang/51e576b3-9cc0-41b5-b87a-32bcd60f2386 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use laquythang/51e576b3-9cc0-41b5-b87a-32bcd60f2386 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Mistral-Nemo-Base-2407") model = PeftModel.from_pretrained(base_model, "laquythang/51e576b3-9cc0-41b5-b87a-32bcd60f2386") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a30b3057810d68f868c7e02f0793fb689faeb7d844440fedc51ff6aee8796201
- Size of remote file:
- 228 MB
- SHA256:
- 25d16e6bca0d16cb180cb5d24ee1b2ee7b7848484080e1cfbf2b6ae488aeaf6d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.