# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("I77/question_classifier")
model = AutoModelForSequenceClassification.from_pretrained("I77/question_classifier")Quick Links
RuBERT Model for Logical Question Classification
This model classifies questions as logically correct or incorrect.
1 - logically correct
0 - logically incorrect
Metrics on validation
Accuracy: 0.9500 Precision: 1.0000 Recall: 0.9000 F1-score: 0.9474
Example inference
from transformers import pipeline
classifier = pipeline('text-classification', model='I77/question_classifier')
print(classifier('Этот вопрос логичен?'))
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Model tree for I77/question_classifier
Base model
DeepPavlov/rubert-base-cased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="I77/question_classifier")