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:
- ac74e514a7f3deb7c4113fcf06c95bc85532efb926675baa1b6f0ddf8ef86fa2
- Size of remote file:
- 6.78 kB
- SHA256:
- 6726373f156b5f72f102e7eba9906a3d53f26689aee4a64c6787bce6aa30b12c
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