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# Imports | |
import gradio as gr | |
from sklearn.linear_model import LogisticRegression | |
import pickle5 as pickle | |
# Load model from pickle file | |
model = pickle.load(open('lg_classifier.sav', 'rb')) | |
# Define function to predict | |
def predict(text): | |
return model.predict([text])[0] | |
# Define interface | |
iface = gr.Interface(fn=predict, | |
inputs=gr.inputs.Textbox(lines=10, label="Input Text"), | |
outputs=gr.outputs.Label(num_top_classes=3), | |
title="Text Classification", | |
description="Classify text as other[0], healthcare[1], or technology[2]", | |
examples=[ | |
['This is a text about healthcare'], | |
['This is a text about technology'], | |
['This is a text about other']], | |
allow_flagging='never' | |
) | |