22 lines
727 B
Python
22 lines
727 B
Python
import gradio as gr
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from transformers import pipeline, AutoTokenizer, AutoConfig, AutoModelForSequenceClassification
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modelName="papluca/xlm-roberta-base-language-detection"
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sentimentPipeline = pipeline("sentiment-analysis", modelName)
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def sentiment_analysis(text):
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results = sentimentPipeline(text)
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return results
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#return f"Sentiment: {results[0].get('label')}, Score: {results[0].get('score'):.2f}"
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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 = "语种分类"
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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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