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
Download adapter_model.safetensors from trangtrannnnn/e031e4af-8a88-4497-ab7d-ebe55bb366d2: direct link, hf CLI and curl.
- Browser
- Download file 83.9 MB
-
https://huggingface.co/trangtrannnnn/e031e4af-8a88-4497-ab7d-ebe55bb366d2/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://trangtrannnnn/e031e4af-8a88-4497-ab7d-ebe55bb366d2/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/trangtrannnnn/e031e4af-8a88-4497-ab7d-ebe55bb366d2/resolve/main/adapter_model.safetensors
83.9 MB
- Xet hash:
- 748083f05caf0277e9de61793a52c61babaa7bb1cb20f55d5727e0cef7fc2e24
- Size of remote file:
- 83.9 MB
- SHA256:
- f9ca4a147e53359edda83a74da3f7ecb0dfae92383a04ab580c902c50998123b
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