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:
- 3d77283b9c1c3212e44860d4726fb5b80cc706b4fa8f37162ffb3fe83feeeaff
- Size of remote file:
- 434 MB
- SHA256:
- b2774f2f91711c2f9c8303aa86b38115bb0155ec980829533eb689fabda96599
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