Instructions to use lhong4759/564d2a64-a9b6-49a4-89b0-5bb236103b8d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/564d2a64-a9b6-49a4-89b0-5bb236103b8d 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, "lhong4759/564d2a64-a9b6-49a4-89b0-5bb236103b8d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 783bf33cca526e7179c02461c573446d27bf68200f358a656ebcfeb07c2757ad
- Size of remote file:
- 84 MB
- SHA256:
- 090cda15ac33e38ec1448b61805d955d8525651bd9aa750552d3bd4a22eb8b99
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