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app.py
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@@ -17,8 +17,13 @@ iface = gr.Interface(
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fn=calculate,
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inputs=gr.inputs.Textbox(lines=5, placeholder="Enter your text here..."),
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outputs=[gr.outputs.Label(num_top_classes=3), "text"],
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title="Sentiment Analysis",
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description="
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)
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iface.launch()
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fn=calculate,
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inputs=gr.inputs.Textbox(lines=5, placeholder="Enter your text here..."),
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outputs=[gr.outputs.Label(num_top_classes=3), "text"],
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title="Sentiment Analysis for Serbian",
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description="""
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This tool performs sentiment analysis on the input text using a model trained on Serbian dictionary definitions.
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The model was initially pretrained on the [sr-gpt2-large model by Mihailo Škorić](https://huggingface.co/JeRTeh/sr-gpt2-large),
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then fine-tuned on selected definitions from the Serbian WordNet. Please limit the input to 300 tokens.
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The outputs represent the Positive (POS), Negative (NEG), and Objective (OBJ) sentiment scores.
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"""
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)
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iface.launch()
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