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| import pickle as pk | |
| import gradio as gr | |
| import numpy as np | |
| import pandas as pd | |
| from sklearn.linear_model import LinearRegression | |
| loaded_model = pk.load(open("score_predict.pkl", "rb"), encoding="bytes") | |
| def predict_my_score(hours_of_study): | |
| input_arr = [[hours_of_study]] | |
| y_predict_new = loaded_model.predict(input_arr) | |
| return int(y_predict_new[0][0]) | |
| interface = gr.Interface(predict_my_score, title = "Predict My Score ", description = "Enter the hours you study per day and know your score.", inputs = "number", outputs = "number") | |
| interface.launch(share = True) |