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Infinitode Pty Ltd
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Update app.py
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app.py
CHANGED
@@ -146,7 +146,7 @@ demo = gr.Interface(
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inputs=[gr.Radio(choices=["Terraria", "Skyrim"], label="Choose a model for your request", value="Terraria"), gr.Slider(1,100, step=1, label='Amount of Names', info='How many names to generate, must be greater than 0'), gr.Slider(10, 60, value=30, step=1, label='Max Length', info='Max length of the generated word'), gr.Slider(0.1, 1, value=0.5, label='Temperature', info='Controls randomness of generation, higher values = more creative, lower values = more probalistic'), gr.Textbox('', label='Seed text (optional)', info='The starting text to begin with', max_lines=1, )],
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outputs=[gr.Dataframe(row_count = (2, "dynamic"), col_count=(1, "fixed"), label="Generated Names", headers=["Names"])],
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title='Dungen - Name Generator',
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description='A fun game-inspired name generator. For an example of how to create, and train your model, similar to this one, head over to: https://github.com/
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demo.launch()
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inputs=[gr.Radio(choices=["Terraria", "Skyrim"], label="Choose a model for your request", value="Terraria"), gr.Slider(1,100, step=1, label='Amount of Names', info='How many names to generate, must be greater than 0'), gr.Slider(10, 60, value=30, step=1, label='Max Length', info='Max length of the generated word'), gr.Slider(0.1, 1, value=0.5, label='Temperature', info='Controls randomness of generation, higher values = more creative, lower values = more probalistic'), gr.Textbox('', label='Seed text (optional)', info='The starting text to begin with', max_lines=1, )],
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outputs=[gr.Dataframe(row_count = (2, "dynamic"), col_count=(1, "fixed"), label="Generated Names", headers=["Names"])],
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title='Dungen - Name Generator',
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description='A fun game-inspired name generator. For an example of how to create, and train your model, similar to this one, head over to: https://github.com/Infinitode/OPEN-ARC/tree/main/Project-5-TWNG. There you will find our base model, the dataset we used, and implementation code in the form of a Jupyter Notebook (exported from Kaggle).'
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demo.launch()
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