Instructions to use beast33/9f2387b3-6a2c-4a8b-957e-e1c917a74ce5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/9f2387b3-6a2c-4a8b-957e-e1c917a74ce5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("beomi/polyglot-ko-12.8b-safetensors") model = PeftModel.from_pretrained(base_model, "beast33/9f2387b3-6a2c-4a8b-957e-e1c917a74ce5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 843b54a268bc43773fc1fbaf90dc48114a9e84abe7564db3339a685ce2c960d0
- Size of remote file:
- 839 MB
- SHA256:
- ed31d5bdba9857e15d93ea6a17da2caea5ce642c5d0dee7a305c536e0e0a06c6
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