Instructions to use daniel40/9d82966a-7d6b-4049-9e8c-b87e50d8768c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daniel40/9d82966a-7d6b-4049-9e8c-b87e50d8768c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Theta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "daniel40/9d82966a-7d6b-4049-9e8c-b87e50d8768c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 977905f2b95e5209ca5b6d2da790c15e045c7e84e3b07fb8322b390f448e2983
- Size of remote file:
- 2.44 GB
- SHA256:
- 867d21822443e017ab02bb37e35da63a90f289cd0f04661d8b652d2cbefba1ef
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