Instructions to use mrHungddddh/eb0a9fe8-88bc-4f9f-9945-8c1674419711 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrHungddddh/eb0a9fe8-88bc-4f9f-9945-8c1674419711 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-2-SOLAR-10.7B") model = PeftModel.from_pretrained(base_model, "mrHungddddh/eb0a9fe8-88bc-4f9f-9945-8c1674419711") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d727798e2a2617913c0c8f19cda8ccc7af7ac0498c06fac6714c66a796855cb
- Size of remote file:
- 126 MB
- SHA256:
- 2d0a42ed21908d39b8c5addf2cc7589c1e074ef3b6ee5b244237560e9d5aafef
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