Instructions to use nhunglaaaaaaa/c3a3dae1-eb8d-4281-ad2d-35c83c8f9a7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhunglaaaaaaa/c3a3dae1-eb8d-4281-ad2d-35c83c8f9a7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "nhunglaaaaaaa/c3a3dae1-eb8d-4281-ad2d-35c83c8f9a7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8bc9da67363be0ec3cdc4c5971b2055dc6dacba3df81a88331c7dc97579c67e
- Size of remote file:
- 37 MB
- SHA256:
- dca715ba7fc003aff2051e288b8dc5c472a1dc942bf020866530445649144731
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