Instructions to use lightsource/gemma2_9b_multilabel_lora_adapter_ver2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lightsource/gemma2_9b_multilabel_lora_adapter_ver2 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("unsloth/gemma-2-9b-it-bnb-4bit") model = PeftModel.from_pretrained(base_model, "lightsource/gemma2_9b_multilabel_lora_adapter_ver2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13e800ab191468b320478ac3fcea5c2711d1e740fe0ab45e198869c4e1999ec4
- Size of remote file:
- 440 MB
- SHA256:
- 1fccaae82545e85b4f4a449342b3ca8256a6fd7954143e240da70748f3978885
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