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:
- 5067e6f88358dec8066dc43a00c09de19b0f7a8e436e59423f3934c5edf05275
- Size of remote file:
- 17.2 MB
- SHA256:
- ade1dac458f86f9bea8bf35b713f14e1bbed24228429534038e9f7e54ea3e8b6
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