Instructions to use eeeebbb2/f82de705-b584-4950-8670-43c7ce2f4f0a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/f82de705-b584-4950-8670-43c7ce2f4f0a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lcw99/zephykor-ko-7b-chang") model = PeftModel.from_pretrained(base_model, "eeeebbb2/f82de705-b584-4950-8670-43c7ce2f4f0a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5331a06a4b060ba96acd3d0bd67535739f7a38ef71bf8ca9bb5df510f1996ed
- Size of remote file:
- 6.84 kB
- SHA256:
- df298e2582d3d6994ac5acc5aec2942f791349a847d925745adcf3ac89e05f95
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