Views
No views yet
classify_text function with a text input, and it will return the predicted class label.1text = "This is a positive review."
2predicted_class = classify_text(text)
3print("Predicted class:", predicted_class)
4
5from transformers import BertTokenizer, BertForSequenceClassification
6
7# Load pre-trained BERT tokenizer and model
8tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
9model = BertForSequenceClassification.from_pretrained('bert-base-uncased')
10
11# Define a function to classify text
12def classify_text(text):
13 inputs = tokenizer(text, return_tensors='pt', padding=True, truncation=True)
14 outputs = model(**inputs)
15 logits = outputs.logits
16 probabilities = logits.softmax(dim=1)
17 predicted_class = probabilities.argmax(dim=1).item()
18 return predicted_class
19
20# Example usage
21text = "This is a positive review."
22predicted_class = classify_text(text)
23print("Predicted class:", predicted_class)