Text Classification
Transformers
TensorBoard
Safetensors
English
bert
dark patterns
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("asquirous/bert-base-uncased-dark_patterns")
model = AutoModelForSequenceClassification.from_pretrained("asquirous/bert-base-uncased-dark_patterns")Quick Links
This model has been trained on a very small dataset having ~1.8k samples and 8 classes. It performs horribly in classifying the type of dark pattern, but I did notice that it performs pretty well in classifying if it is a dark pattern or not. That is, it outputs "Not Dark Pattern" accurately most of the times (formal evaluation not done) when the given text is not a dark pattern (according to the examples in the dataset) and any of the other labels otherwise.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="asquirous/bert-base-uncased-dark_patterns")