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:
- 44ad7f5b35029048fd87cd11b783ecd54c57e2d004c8742a5f5502b7f91d8ea2
- Size of remote file:
- 84 MB
- SHA256:
- 890c2b485eab3a2d3deb803e295340f00261f51f99ec7c91af39d8575e1b246f
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