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:
- e7f44af613ed081993254d8329c169aa7dd9a319e7e2cae910821ad5683c0d3b
- Size of remote file:
- 2.44 GB
- SHA256:
- 3d59d9c41483d249bc36f87527fd19dcdaaaba1b455c0bfc0938760ee6b03d06
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