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:
- fde8653f2f656fb4ab30c2a5db64ba86a916a86134355b76c3bf26a5b022b323
- Size of remote file:
- 4.24 MB
- SHA256:
- 61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
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