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:
- 8fb62716fb6a40b49125728e65e79f22387b1ec819af2824824ba242a3f7de38
- Size of remote file:
- 83.9 MB
- SHA256:
- 4b6961ec56fb4a44ef494b0d658571c48ac344664dc6fe4a951f2610f0f03b8f
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