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# Imports | |
import gradio as gr | |
from sklearn.linear_model import LogisticRegression | |
import pickle5 as pickle | |
# file name | |
lr_filename = 'lg_classifier.sav' | |
# Load model from pickle file | |
model = pickle.load(open(lr_filename, 'rb')) | |
# Define function to make a prediction with the model | |
def predict(text): | |
return model.predict([text])[0] | |
# Define interface | |
demo = gr.Interface(fn=predict, | |
title="Text Classification Demo", | |
description="This is a demo of a text classification model using Logistic Regression.", | |
inputs=gr.Textbox(lines=10, placeholder='Input text here...', label="Input Text"), | |
outputs=gr.Textbox(label="Predicted Label", lines=2, placeholder='Predicted label will appear here...'), | |
allow_flagging='never' | |
) | |
demo.launch() | |