updating data paths
Browse files
app.py
CHANGED
@@ -32,36 +32,36 @@ with demo:
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with gr.TabItem("Text Generation π¬"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/text_generation.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/text_generation.csv'))
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with gr.TabItem("Image Generation π·"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/image_generation.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/image_generation.csv'))
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with gr.TabItem("Text Classification π"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/text_classification.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/text_classification.csv'))
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with gr.TabItem("Image Classification πΌοΈ"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/image_classification.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/image_classification.csv'))
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with gr.TabItem("Extractive QA β"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/question_answering.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/question_answering.csv'))
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demo.launch()
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with gr.TabItem("Text Generation π¬"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/energy/text_generation.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/energy/text_generation.csv'))
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with gr.TabItem("Image Generation π·"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/energy/image_generation.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/energy/image_generation.csv'))
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with gr.TabItem("Text Classification π"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/energy/text_classification.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/energy/text_classification.csv'))
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with gr.TabItem("Image Classification πΌοΈ"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/energy/image_classification.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/image_classification.csv'))
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with gr.TabItem("Extractive QA β"):
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with gr.Row():
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with gr.Column():
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plot = gr.Plot(get_plots('data/energy/question_answering.csv'))
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with gr.Column():
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table = gr.Dataframe(get_model_names('data/energy/question_answering.csv'))
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demo.launch()
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