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grouping.
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app.py
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@@ -61,29 +61,34 @@ with block:
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</div>
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"""
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gr.
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<ul>
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</ul>
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<li>Increasing both the number of images per prompt and the number of inference steps could quickly build up the inference queue and thus
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resulting in slowdowns.</li>
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</ul>
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</p>
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</div>
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"""
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block.launch()
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</div>
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"""
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with gr.Group():
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# with gr.Box():
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# with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
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# with gr.Column():
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# gr.Text(max_lines=1, placeholder="a painting of a dog")
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gr.HTML(
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"""
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<div class="acknowledgments">
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<p><h4>How it works?</h4>
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<ul>
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<li> The evaluator first sets a seed and then generates the initial noise which is passed as the initial latent to start the image generation process. It is done to ensure fair comparison.</li>
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<li>This initial latent is used every time the pipeline is run (with different schedulers).</li>
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<li>To quantify the quality of the generated images we use:</li>
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<ul>
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<li><a href=https://en.wikipedia.org/wiki/Inception_score>Inception Score</a></li>
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<li><a href=https://arxiv.org/abs/2104.08718>Clip Score</a></li>
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</ul>
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</ul></p>
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<p><h4>Notes</h4>
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<ul>
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<li>The default scheduler associated with the provided checkpoint is always used for reporting the scores.</li>
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<li>Increasing both the number of images per prompt and the number of inference steps could quickly build up the inference queue and thus
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resulting in slowdowns.</li>
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</ul>
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</p>
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</div>
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"""
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block.launch()
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