27 lines
764 B
Python
27 lines
764 B
Python
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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="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True)
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def sentiment_analysis(text):
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results = classifier(text)
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total_result = ""
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for result in results[0]:
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total_result += f"Sentiment: {result.get('label')}, Score: {result.get('score'):.2f}"
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total_result += '\r\n'
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return total_result
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demo = gr.Interface(fn=sentiment_analysis,
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inputs='text',
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outputs='text',
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title = "文本情感分析"
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)
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if __name__ == "__main__":
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demo.queue(concurrency_count=3)
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demo.launch(server_name = "0.0.0.0", server_port = 7028)
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