Instructions to use mrHungddddh/6670f094-938d-4b20-ac7f-4aceb28e31d2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrHungddddh/6670f094-938d-4b20-ac7f-4aceb28e31d2 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, "mrHungddddh/6670f094-938d-4b20-ac7f-4aceb28e31d2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68460930531cd408d1d7e6be64c323e52c08f50158affc7ba72dd5103880d8df
- Size of remote file:
- 83.9 MB
- SHA256:
- ec9b3c633e16ebf27e4ea0beec660904c0f73f5b01ab3e9fd9a44b4be1504de8
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