| import pickle | |
| from sklearn.feature_extraction.text import TfidfVectorizer | |
| # Cargar el modelo y el vectorizador | |
| with open('vectorizer.pkl', 'rb') as f: | |
| vectorizer = pickle.load(f) | |
| with open('model.pkl', 'rb') as f: | |
| model = pickle.load(f) | |
| def predict(text): | |
| # Preprocesar el texto usando el vectorizador | |
| X = vectorizer.transform([text]) | |
| # Hacer una predicción usando el modelo | |
| return model.predict(X) | |