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Update app.py
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app.py
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@@ -27,12 +27,20 @@ def documentation():
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return """
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## Sentiment Analysis Documentation
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This demo utilizes two different models from the Hugging Face Transformers library:
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- **Model 1**: RoBERTa-large for sentiment analysis fine-tuned for diverse English text sources to enhance generalization across different types of texts (reviews, tweets, etc.).
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- **Model 2**: BERTweet for sentiment analysis specifically fine-tuned for English Tweets.
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"""
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with gr.Blocks(title="Sentiment Analysis", theme=gr.themes.Soft()) as demo:
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return """
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## Sentiment Analysis Documentation
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Welcome to the Sentiment Analysis Demo! This interactive application leverages advanced machine learning models to analyze and predict the sentiment of the text you provide.
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### About the Technology
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Sentiment analysis is a branch of artificial intelligence that involves the computational identification and categorization of sentiment expressed in written language. The underlying models are trained on large datasets with various annotations to learn how to predict sentiment accurately.
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This demo utilizes two different models from the Hugging Face Transformers library:
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- **Model 1**: RoBERTa-large for sentiment analysis fine-tuned for diverse English text sources to enhance generalization across different types of texts (reviews, tweets, etc.).
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- **Model 2**: BERTweet for sentiment analysis specifically fine-tuned for English Tweets.
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### Data Privacy
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We value your privacy. All input texts are processed in real-time and are not stored or used for any purpose other than sentiment analysis during your session.
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Enjoy exploring the nuances of sentiment in text with our cutting-edge AI models! 🙂
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"""
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with gr.Blocks(title="Sentiment Analysis", theme=gr.themes.Soft()) as demo:
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