Instructions to use cunghoctienganh/8c90369c-2790-4372-a0e2-a9bf8d59d753 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cunghoctienganh/8c90369c-2790-4372-a0e2-a9bf8d59d753 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, "cunghoctienganh/8c90369c-2790-4372-a0e2-a9bf8d59d753") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff6679eba411a9d2b1b3277fa7efc7ac28d668363dea1da0bd922b0f1571693d
- Size of remote file:
- 6.78 kB
- SHA256:
- 09e0812d159efba38e07392add7db5090e1fa3f45f8de9b3cecfb45bc321d451
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