Instructions to use cimol/ee84fe34-f20a-40f9-8bc4-745baa3fbebe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/ee84fe34-f20a-40f9-8bc4-745baa3fbebe with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "cimol/ee84fe34-f20a-40f9-8bc4-745baa3fbebe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47cbbc612c4f0133c52d9bfb7fe69a76c5b80c97ffe70b0362401e25404dd82e
- Size of remote file:
- 671 MB
- SHA256:
- ad2e22fb7d43331eb8be047df1c8978b49832a92953c26f1129d281f29c32d9b
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