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import gradio as gr |
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from transformers import pipeline |
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classifier = pipeline("text-classification",model='bhadresh-savani/distilbert-base-uncased-emotion', return_all_scores=True) |
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def detect_emotions(emotion_input): |
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prediction = classifier(emotion_input,) |
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output = {} |
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for emotion in prediction[0]: |
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output[emotion["label"]] = emotion["score"] |
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return output |
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examples = [["I am excited to announce that I have been promoted"], ["Sorry for the late reply"]] |
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demo = gr.Interface(fn=detect_emotions, inputs=gr.Textbox(placeholder="Enter text here", label="Input"), outputs=gr.Label(label="Emotion"), examples=examples) |
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demo.launch() |