Instructions to use trangtrannnnn/e031e4af-8a88-4497-ab7d-ebe55bb366d2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/e031e4af-8a88-4497-ab7d-ebe55bb366d2 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, "trangtrannnnn/e031e4af-8a88-4497-ab7d-ebe55bb366d2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bafeb1ec7e6fa8239a91c47e4890b2d9802fe42cec0e7331c5b9efdcf8814d57
- Size of remote file:
- 6.78 kB
- SHA256:
- d5e0369985dd3c12cef9d07c08961d65bf89929b3a4480ad806c02cc747a855d
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