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Update app.py
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app.py
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import gradio as gr
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def greet(name):
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iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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iface.launch()
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import gradio as gr
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import tensorflow as tf
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import numpy as np
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import pickle
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# Load model, including its weights and the optimizer
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model = tf.keras.models.load_model('core4.h5')
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# load tokenizer
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with open('tokenizer.pickle', 'rb') as handle:
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tokenize = pickle.load(handle)
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text_labels = ['How to apply', 'how much can I get', 'who can apply']
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# model.summary() # model architecture
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def greet(name):
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tokenizedText = tokenize.texts_to_matrix([string])
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prediction = model.predict(np.array([tokenizedText[0]]))
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predicted_label = text_labels[np.argmax(prediction)]
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print(prediction[0][np.argmax(prediction)])
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print("Predicted label: " + predicted_label + "\n")
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return predicted_label
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#One testing case
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iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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iface.launch()
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