Instructions to use dzanbek/19e3d005-4ac9-43e6-8bd4-ea36d19e41ea with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/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, "dzanbek/19e3d005-4ac9-43e6-8bd4-ea36d19e41ea") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 366c2e21381dfea8ae07719838707b89699a2e49c19028ef18561e88cedb908f
- Size of remote file:
- 336 MB
- SHA256:
- 2f9945e105c9ca885e4d3510adbc129ebd94a69b62945924e4dd1bb85987a97c
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