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Update app.py
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app.py
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@@ -9,7 +9,7 @@ import time
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resolutions = ["1024 1024","1280 768","1344 768","768 1344","768 1280"]
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# Ng
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default_negative_prompt= "Logo,
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pipe = BriaPipeline.from_pretrained("briaai/BRIA-3.1", torch_dtype=torch.bfloat16,trust_remote_code=True)
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pipe.to(device="cuda")
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@@ -58,12 +58,11 @@ with gr.Blocks(css=css) as demo:
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<p style="margin-bottom: 10px; font-size: 94%">
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This is a demo for
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<a href="https://huggingface.co/briaai/BRIA-3.1" target="_blank">BRIA 3.1 text-to-image </a>.
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</p>
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''')
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with gr.Group():
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with gr.Column():
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prompt_in = gr.Textbox(label="Prompt", value="
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resolution = gr.Dropdown(value=resolutions[0], show_label=True, label="Resolution", choices=resolutions)
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seed = gr.Textbox(label="Seed", value=-1)
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negative_prompt = gr.Textbox(label="Negative Prompt", value=default_negative_prompt)
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resolutions = ["1024 1024","1280 768","1344 768","768 1344","768 1280"]
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# Ng
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default_negative_prompt= "Logo,Ugly,Morbid,Extra fingers,Poorly drawn hands,Mutation,Blurry,Extra limbs,Gross proportions,Missing arms,Mutated hands,Long neck,Duplicate,Mutilated,Mutilated hands,Poorly drawn face,Deformed,Bad anatomy,Cloned face,Malformed limbs,Missing legs,Too many fingers"
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pipe = BriaPipeline.from_pretrained("briaai/BRIA-3.1", torch_dtype=torch.bfloat16,trust_remote_code=True)
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pipe.to(device="cuda")
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<p style="margin-bottom: 10px; font-size: 94%">
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This is a demo for
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<a href="https://huggingface.co/briaai/BRIA-3.1" target="_blank">BRIA 3.1 text-to-image </a>.
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is our new text-to-image model that achieves high-quality generation while being trained exclusively on fully licensed data. We offer both API access and direct access to the model weights, making integration seamless for developers. </p>
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''')
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with gr.Group():
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with gr.Column():
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prompt_in = gr.Textbox(label="Prompt", value="photo of mystical dragon eating sushi, text bubble says "Sushi Time".")
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resolution = gr.Dropdown(value=resolutions[0], show_label=True, label="Resolution", choices=resolutions)
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seed = gr.Textbox(label="Seed", value=-1)
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negative_prompt = gr.Textbox(label="Negative Prompt", value=default_negative_prompt)
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