Instructions to use lhong4759/19e3d005-4ac9-43e6-8bd4-ea36d19e41ea with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/19e3d005-4ac9-43e6-8bd4-ea36d19e41ea with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "lhong4759/19e3d005-4ac9-43e6-8bd4-ea36d19e41ea") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cab19508d947459955b5012d7dfdefb624783bdc8c2b8af7291cf7c0b096896
- Size of remote file:
- 6.78 kB
- SHA256:
- 0427d01c50e134c324cc48e172e44075dda9bfc274d167c8578b92368d4b4476
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