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:
- 3dd855559a96b0da3115ab4168f11ad022e9d08adbd1c4138a208be4cc0a16e0
- Size of remote file:
- 6.71 kB
- SHA256:
- 3f40a71cc25786961be932d28df4d4b5e901fcf1f5c719f4b612f7b6c5233d51
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