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:
- 3c6f0f9949af6ab9fa24e8cc1398e2b46b1a448d7f383c53a980dcf7c8c9cfe3
- Size of remote file:
- 6.78 kB
- SHA256:
- 1aa6cbe24bdd44000c03e6e9e82be43e70da38a16bb1824dc422a596dd2afae2
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