Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("afg1/sentence_contraditcion_model")
model = AutoModelForSequenceClassification.from_pretrained("afg1/sentence_contraditcion_model", device_map="auto")Quick Links
A model to detect contradictory sentences.
Based on the MSc thesis of Beatriz Souto de Sá Baldaia, which you can read here: https://repositorio-aberto.up.pt/bitstream/10216/129029/2/415679.pdf
I repackaged the datasets used and fine-tuned from distilbert-base-uncased. Thanks Kaggle for the compute!
Datasets can be found in their original format here: https://github.com/BeatrizBaldaia/sentence-pair-contradictions/tree/master
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afg1/sentence_contraditcion_model")