Instructions to use FMZGL/Gemma2-9b-cv93 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FMZGL/Gemma2-9b-cv93 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("/root/autodl-tmp/model/gemma2-9b-it-bf16") model = PeftModel.from_pretrained(base_model, "FMZGL/Gemma2-9b-cv93") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a784399e4bd94057d473b769e8cf3426797ccc2029a6e05560fec13277cd8f35
- Size of remote file:
- 34.4 MB
- SHA256:
- 33e0fd4dd56d771210156237eee1daaebae62484d907431899bad6b5e1e61fa4
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