Instructions to use vmpsergio/388fced2-7194-4f76-84cc-5abb47ae505f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/388fced2-7194-4f76-84cc-5abb47ae505f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "vmpsergio/388fced2-7194-4f76-84cc-5abb47ae505f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7543cf2d5ba21a14b71331e1842a43cdd0ac2d9b9fd8291116f91c191c66125f
- Size of remote file:
- 6.78 kB
- SHA256:
- 2aadb4cfc3a74d5099cfe4cc806ff480d5d0e533c31df74d59f1baf28fb20b12
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