Instructions to use paduraru2009/distilbert-base-uncased-sentimentanalysis-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use paduraru2009/distilbert-base-uncased-sentimentanalysis-demo with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased") model = PeftModel.from_pretrained(base_model, "paduraru2009/distilbert-base-uncased-sentimentanalysis-demo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6cb5200d8d80b1230268832293cfbcee498d6949aab20d424c0c1d7216a43c6
- Size of remote file:
- 2.67 MB
- SHA256:
- 50732b4f60cc53eb80b82376f94647567ab4577f778b706ac86550d20c4803eb
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