Instructions to use cwaud/fcb794f8-87e5-450a-803b-1de44a075f71 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cwaud/fcb794f8-87e5-450a-803b-1de44a075f71 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MLP-KTLim/llama-3-Korean-Bllossom-8B") model = PeftModel.from_pretrained(base_model, "cwaud/fcb794f8-87e5-450a-803b-1de44a075f71") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd5aefcf1fa86c8cd5921621cade75d66fae1e4fd19a9fd1f16eaf82fb007f70
- Size of remote file:
- 6.71 kB
- SHA256:
- 9cbb2f2e45b3a43149649a9cd562f1c6ef9c844a6ca5f0b76e3b2e03a1b8ab5f
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