Instructions to use cimol/94bee815-bb95-47e6-835f-ad38135a2860 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/94bee815-bb95-47e6-835f-ad38135a2860 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("samoline/5cf4792e-00af-4d5f-b922-4c7d5237f306") model = PeftModel.from_pretrained(base_model, "cimol/94bee815-bb95-47e6-835f-ad38135a2860") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aec02e3de6e2fb589a4d7d5d9fb5e43c2a78218835377aa4b332dce1bba0eaf9
- Size of remote file:
- 6.84 kB
- SHA256:
- ed1608a5321241e9a40a6e63304730324b0105623d214842c5fdc4e8c0efbc6b
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