Instructions to use Venkatesh4342/quantized-dark_pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Venkatesh4342/quantized-dark_pattern with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Venkatesh4342/quantized-dark_pattern")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Venkatesh4342/quantized-dark_pattern") model = AutoModelForSequenceClassification.from_pretrained("Venkatesh4342/quantized-dark_pattern", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42ed561252135f6756cae7e7ec7c0ad04cd19669ab3f9f0ba8c4715f579ace05
- Size of remote file:
- 82.6 MB
- SHA256:
- 813d715825554a250f71d03b93ef3040c2715c52446003ea4b71e8c5901ad3e4
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