Instructions to use jeongyoonhuh/q_lora_korqa_re with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jeongyoonhuh/q_lora_korqa_re with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-4b-it") model = PeftModel.from_pretrained(base_model, "jeongyoonhuh/q_lora_korqa_re") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jeongyoonhuh/q_lora_korqa_re: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/jeongyoonhuh/q_lora_korqa_re/resolve/main/training_args.bin
- Command line
-
hf download hf://jeongyoonhuh/q_lora_korqa_re/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jeongyoonhuh/q_lora_korqa_re/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- a3288eed273ebb45c84f2077c11b4cc2e4fb723854a6fb770da16aa11373cfdb
- Size of remote file:
- 5.24 kB
- SHA256:
- 397d33c02930459e5f249b114462600d30d6bd219204dba10b2570a68569ae34
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