28 lines
793 B
Python
28 lines
793 B
Python
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import gradio as gr
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from transformers import pipeline
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unmasker = pipeline('fill-mask', model='bert-base-uncased')
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def sentiment_analysis(text):
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results = unmasker(text)
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total_results = ""
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for result in results:
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total_results += f"Token: {result.get('token_str')}, Score: {result.get('score')}"
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total_results += '\r\n'
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return total_results
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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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examples=[['Paris is the [MASK] of France.'], ['The goal of life is [MASK].']],
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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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