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app.py
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@@ -24,6 +24,7 @@ with gr.Blocks() as demo:
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<div style="display: block; text-align: left; padding:0; margin:0;font-family: "Source Sans Pro", Helvetica, sans-serif;">
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<h1 style="text-align: center;font-size: 17pt;">Babel Machine Demo</h1>
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<p style="font-size: 14pt;">This is a demo for text classification using language models finetuned on data labeled by <a href="https://www.comparativeagendas.net/">CAP</a>, <a href="https://manifesto-project.wzb.eu/">Manifesto Project</a>, sentiment, emotion coding and Named Entity Recognition systems.<br>
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For the coding of complete datasets, please visit the official <a href="https://babel.poltextlab.com/">Babel Machine</a> site.<br>
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Please note that named entity inputs are case sensitive.<br>
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</p>
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<div style="display: block; text-align: left; padding:0; margin:0;font-family: "Source Sans Pro", Helvetica, sans-serif;">
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<h1 style="text-align: center;font-size: 17pt;">Babel Machine Demo</h1>
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<p style="font-size: 14pt;">This is a demo for text classification using language models finetuned on data labeled by <a href="https://www.comparativeagendas.net/">CAP</a>, <a href="https://manifesto-project.wzb.eu/">Manifesto Project</a>, sentiment, emotion coding and Named Entity Recognition systems.<br>
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Please note that the sentiment (3) and emotions (8) models have been trained using parliamentary speech data, so the results for generic sentences are not reliable.<br>
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For the coding of complete datasets, please visit the official <a href="https://babel.poltextlab.com/">Babel Machine</a> site.<br>
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Please note that named entity inputs are case sensitive.<br>
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</p>
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