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:
- bf2f790843428a4cc5249956d53fd88cc8b05a28f2d7959f0df1ffca9140d875
- Size of remote file:
- 839 MB
- SHA256:
- 808ad3315a674f9bf55fb944bdcd6f2b46c9615b101e7051c9d875a4e69f3be9
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