Instructions to use mrHunghddddd/6131463a-4253-4336-82ce-7292b28875e7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrHunghddddd/6131463a-4253-4336-82ce-7292b28875e7 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, "mrHunghddddd/6131463a-4253-4336-82ce-7292b28875e7") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from mrHunghddddd/6131463a-4253-4336-82ce-7292b28875e7: direct link, hf CLI and curl.
- Browser
- Download file 83.9 MB
-
https://huggingface.co/mrHunghddddd/6131463a-4253-4336-82ce-7292b28875e7/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://mrHunghddddd/6131463a-4253-4336-82ce-7292b28875e7/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/mrHunghddddd/6131463a-4253-4336-82ce-7292b28875e7/resolve/main/adapter_model.safetensors
83.9 MB
- Xet hash:
- 82be5706d510a9afca46581ed0cad47efbb47e5e3f076ecc7904525d434092bc
- Size of remote file:
- 83.9 MB
- SHA256:
- ff584cb13c8659db8263f6d02ac76ae82b5f77d33fdcb604a4b1aa6bce11fa70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.