# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("orisuchy/Descriptive_Classifier")
model = AutoModelForSequenceClassification.from_pretrained("orisuchy/Descriptive_Classifier")Quick Links
Descriptive Sentences Classifier
Based on AlephBERT model.
Metrics
accuracy: 0.813953488372093
f1: 0.8181818181818182
How to Use the model:
from transformers import pipeline
classifier = pipeline("text-classification",model='orisuchy/Descriptive_Classifier', return_all_scores=True)
outputs = classifier("מסווג חתיך במיוחד")
print(outputs)
"""
Output:
[[
{'label': 'Descriptive', 'score': 0.999764621257782},
{'label': 'Not Descriptive', 'score': 0.00023541577684227377}]]
"""
Or, if you want only the final class:
from transformers import pipeline
classifier = pipeline("text-classification",model='orisuchy/Descriptive_Classifier')
output = classifier("הלכתי אליו הביתה וחיכיתי")
print(output)
"""
Output:
[{'label': 'Not Descriptive', 'score': 0.999901533126831}]
"""
Created by Daniel Smotritsky & Ori Suchy
GitHub
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="orisuchy/Descriptive_Classifier")