kedimestan
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Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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# Load the model and tokenizer
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classifier = pipeline("text-classification",model="AbraMuhara/Fine-TunedBERTURKOfansifTespit")
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# Define the prediction function
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def classify_text(text):
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# Use the pipeline to classify the text
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result = classifier(text)
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# Extract the label and score
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label = result[0]['label']
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score = result[0]['score']
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return f"Label: {label}\nScore: {score:.4f}"
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# Create the Gradio interface
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iface = gr.Interface(
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fn=classify_text, # The function to call for predictions
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inputs=gr.Textbox(), # Text input box
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outputs=gr.Text(), # Text output box
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title="Text Classification", # Title of the app
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description="Enter text to classify it and get the prediction label and score." # Description
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)
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# Launch the interface
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iface.launch()
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