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:
- 92463f4c756056727e926e73a4a0bdb138ba899a04bf8213e514e1fda93ab2d0
- Size of remote file:
- 14.2 kB
- SHA256:
- 386fcc8cc1089aade9450d86fb239ea3483f455fd2d78d8378645feecfec9d69
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