Instructions to use masatochi/tuning-364a1e79-e5ec-4e64-ad45-fd532a9c377e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use masatochi/tuning-364a1e79-e5ec-4e64-ad45-fd532a9c377e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("shenzhi-wang/Llama3.1-8B-Chinese-Chat") model = PeftModel.from_pretrained(base_model, "masatochi/tuning-364a1e79-e5ec-4e64-ad45-fd532a9c377e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acb76cc0bbc6ccfe45984c6854abd85c6fb876ee4478fdf20549368269b7e5a1
- Size of remote file:
- 1.06 kB
- SHA256:
- a35430a05f2b9748f37dd11667a782564c85a35d840d60cbaddfa2c905ab7c0a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.