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:
- 3c0f380e45243bf755f10df4d64525c02e9dc4d30b5c6a9906ba8db50f9a215c
- Size of remote file:
- 168 MB
- SHA256:
- ba7997fbaddecce948f977eafff62e9200373ec8b74d5586d59f08fc5f33ab84
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