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import gradio as gr |
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from transformers import pipeline |
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model = pipeline("text-classification", model="mdeniz1/turkish-sentiment-analysis-bert-base-turkish-uncased") |
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def predict(prompt): |
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sentiment=model(prompt) |
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if sentiment[0]['label']=='LABEL_2': |
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return 'positive' |
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elif sentiment[0]['label']=='LABEL_1': |
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return 'neutral' |
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else: |
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return 'negative' |
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title = "Turkish Sentiment Analysis" |
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description = """ |
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The bot has been trained to analyze the sentiment of Turkish text. When provided with a Turkish prompt, it can determine whether the text expresses a neutral, negative, or positive sentiment. |
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""" |
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textbox = gr.Textbox(label="Enter a text here:", lines=1) |
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gr.Interface( |
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fn=predict, |
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inputs=textbox, |
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outputs="text", |
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title=title, |
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description=description, |
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examples=[["ortam oldukça güzel"], ["senden bir cacık olmaz"]], |
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).launch() |