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app.py
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@@ -83,8 +83,8 @@ st.markdown("""
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5. π **Text summarization** - Automatically summarize large volumes of text. [Example](https://huggingface.co/spaces/awacke1/Text-summarization)
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6. β **Question answering** - Answer questions posed in natural language. [Example](https://huggingface.co/spaces/awacke1/Question-answering)
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7. π€ **Sentiment-aware chatbots** - Use sentiment analysis to detect user emotions and respond appropriately.
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8. π **Text classification** - Classify text into different categories. [Example](https://huggingface.co/spaces/awacke1/
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9. π¬ **Text generation** - Generate natural language text. [Example](https://huggingface.co/spaces/awacke1/
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10. π **Topic modeling** - Automatically identify topics in a large corpus of text. [Example](https://huggingface.co/spaces/awacke1/Topic-modeling)
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- Examples
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1. NLP Video Summary: https://huggingface.co/spaces/awacke1/Video-Summary
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5. π **Text summarization** - Automatically summarize large volumes of text. [Example](https://huggingface.co/spaces/awacke1/Text-summarization)
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6. β **Question answering** - Answer questions posed in natural language. [Example](https://huggingface.co/spaces/awacke1/Question-answering)
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7. π€ **Sentiment-aware chatbots** - Use sentiment analysis to detect user emotions and respond appropriately.
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8. π **Text classification** - Classify text into different categories. [Example](https://huggingface.co/spaces/awacke1/sileod-deberta-v3-base-tasksource-nli)
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9. π¬ **Text generation** - Generate natural language text. [Example](https://huggingface.co/spaces/awacke1/Sentence2Paragraph)
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10. π **Topic modeling** - Automatically identify topics in a large corpus of text. [Example](https://huggingface.co/spaces/awacke1/Topic-modeling)
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- Examples
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1. NLP Video Summary: https://huggingface.co/spaces/awacke1/Video-Summary
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