Instructions to use brildev7/gemma-7b-it-summarization-ko-sft-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use brildev7/gemma-7b-it-summarization-ko-sft-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "brildev7/gemma-7b-it-summarization-ko-sft-qlora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 293412c4324dca5046acf5fbf81f329fc461862718dbacda057a7d80ce47eb98
- Size of remote file:
- 100 MB
- SHA256:
- 7f1c675a2b389818af6cfb0570b921d0d7ddeee776e339173342994e05b611ac
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