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import gradio as gr |
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from huggingface_hub import InferenceClient |
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from transformers import pipeline |
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sentiment = pipeline("text-classification", model="tabularisai/multilingual-sentiment-analysis") |
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""" |
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For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference |
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""" |
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") |
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def get_sentiment(text): |
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output = sentiment(text) |
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return f'The sentence was classified as "{output[0]["label"]}" with {output[0]["score"]*100}% confidence' |
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""" |
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface |
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""" |
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title = "Get a sentiment on you text" |
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description = """ |
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The bot was takes your text and classify it as either 'Positive' or 'Negative' |
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""" |
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demo = gr.Interface( |
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fn=get_sentiment, |
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inputs="text", |
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outputs="text", |
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title=title, |
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description=description, |
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examples=[["I really enjoyed my stay !"], ["Worst rental I ever got"]], |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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