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:
- 65f25055a7b7625641fbc1b0e05d527ed5b3de39ce34638ea7cb385eb98e5943
- Size of remote file:
- 200 MB
- SHA256:
- f37432eee5a610f4d75713ca1849149c82bf195976004fcd4552b6ba9ccd7dd3
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