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import gradio as gr | |
import numpy as np | |
#loading the saved model | |
from keras.models import load_model | |
model = load_model('model.h5') | |
import gradio as gr | |
def page(word): | |
word_tk= tokenizer.texts_to_sequences([word]) | |
word_pad= pad_sequences(word_tk, maxlen=10) | |
prediction = model.predict(word_pad) | |
f_prediction= np.argmax(prediction) | |
if f_prediction == 1: | |
return "Authentic" | |
elif f_prediction ==2: | |
return "Normal" | |
elif f_prediction ==3: | |
return "Not Authentic" | |
else: | |
return "Error" | |
s | |
demo = gr.Interface( | |
fn=page, | |
inputs=gr.Textbox(placeholder="Enter your review and the rating to check the authenticity of any product or page"), | |
outputs="text", | |
) | |
demo.launch() | |
#end |