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:
- d5ffd67d3729f050af7fd259262cf0da261f4e4cad275647749b66c5f7acf48d
- Size of remote file:
- 336 MB
- SHA256:
- 74354de2f6d6664fb1575d58c3bae578386a8224538f7511168aed6316276906
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