Instructions to use JeswinMS4/quantized-dark_pattern2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeswinMS4/quantized-dark_pattern2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeswinMS4/quantized-dark_pattern2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeswinMS4/quantized-dark_pattern2") model = AutoModelForSequenceClassification.from_pretrained("JeswinMS4/quantized-dark_pattern2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8c3e4ce03c4f8ef24187c0f4ed19ac4e5102313e6a3a13aaa92842031809225
- Size of remote file:
- 82.6 MB
- SHA256:
- fc3f3b14e8bbf3cdfd77fb60044b8b73f03156c68b5cddfbfee34cfd455239a2
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