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	Update app.py
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        app.py
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    | @@ -10,7 +10,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu" | |
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            scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False)
         | 
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            pipeline = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True, scheduler=scheduler).to(device)
         | 
| 12 |  | 
| 13 | 
            -
            def run(image, src_style, src_prompt, prompts, shared_score_shift, shared_score_scale, guidance_scale, num_inference_steps, large, seed):
         | 
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                prompts = prompts.splitlines()
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                dim, d = (1024, 128) if large else (512, 64)
         | 
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                image = image.resize((dim, dim))
         | 
| @@ -40,9 +40,10 @@ def run(image, src_style, src_prompt, prompts, shared_score_shift, shared_score_ | |
| 40 | 
             
                return images_a
         | 
| 41 |  | 
| 42 | 
             
            with gr.Blocks() as demo:
         | 
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            -
                gr.Markdown('''# Welcome to | 
| 44 | 
            -
                Here you can generate images with a style from a reference image using [transfer style from sdxl](https://huggingface.co/docs/diffusers/main/en/using-diffusers/sdxl). Add a reference picture, describe the style and add prompts to generate images in that style. It's the most interesting with your own art! | 
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            -
             | 
|  | |
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                with gr.Row():
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                    image_input = gr.Image(label="Reference image", type="pil")
         | 
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                with gr.Row():
         | 
| @@ -51,12 +52,11 @@ with gr.Blocks() as demo: | |
| 51 | 
             
                    prompts_input = gr.Textbox(label="Prompts to generate images (separate with new lines)", lines=5)
         | 
| 52 | 
             
                with gr.Accordion(label="Advanced Settings"):
         | 
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                    with gr.Row():
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            -
                        shared_score_shift_input = gr.Slider(value=1. | 
| 55 | 
            -
                        shared_score_scale_input = gr.Slider(value= | 
| 56 | 
             
                        guidance_scale_input = gr.Slider(value=10.0, label="guidance_scale", minimum=5.0, maximum=20.0, step=1)
         | 
| 57 | 
             
                        num_inference_steps_input = gr.Slider(value=12, label="num_inference_steps", minimum=1, maximum=12, step=1)
         | 
| 58 | 
            -
                         | 
| 59 | 
            -
                        seed_input = gr.Slider(value=0, label="seed (0 for random)", minimum=0, maximum=1000000, step=42)
         | 
| 60 | 
             
                with gr.Row():
         | 
| 61 | 
             
                    run_button = gr.Button("Generate Images")
         | 
| 62 | 
             
                with gr.Row():
         | 
| @@ -64,7 +64,7 @@ with gr.Blocks() as demo: | |
| 64 |  | 
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                run_button.click(
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                    run,
         | 
| 67 | 
            -
                    inputs=[image_input, style_input, image_desc_input, prompts_input, shared_score_shift_input, shared_score_scale_input, guidance_scale_input, num_inference_steps_input,  | 
| 68 | 
             
                    outputs=output_gallery
         | 
| 69 | 
             
                )
         | 
| 70 |  | 
|  | |
| 10 | 
             
            scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False)
         | 
| 11 | 
             
            pipeline = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True, scheduler=scheduler).to(device)
         | 
| 12 |  | 
| 13 | 
            +
            def run(image, src_style, src_prompt, prompts, shared_score_shift, shared_score_scale, guidance_scale, num_inference_steps, large=True, seed):
         | 
| 14 | 
             
                prompts = prompts.splitlines()
         | 
| 15 | 
             
                dim, d = (1024, 128) if large else (512, 64)
         | 
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                image = image.resize((dim, dim))
         | 
|  | |
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                return images_a
         | 
| 41 |  | 
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            with gr.Blocks() as demo:
         | 
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            +
                gr.Markdown('''# Welcome to🌟Tonic's🤵🏻Style📐Align 
         | 
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            +
                Here you can generate images with a style from a reference image using [transfer style from sdxl](https://huggingface.co/docs/diffusers/main/en/using-diffusers/sdxl). Add a reference picture, describe the style and add prompts to generate images in that style. It's the most interesting with your own art! You can also use [stabilityai/stable-diffusion-xl-base-1.0] by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic1/TonicsStyleAlign?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> 
         | 
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            +
            Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/nXx5wbX9) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)
         | 
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            +
            ''')
         | 
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                with gr.Row():
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                    image_input = gr.Image(label="Reference image", type="pil")
         | 
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                with gr.Row():
         | 
|  | |
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                    prompts_input = gr.Textbox(label="Prompts to generate images (separate with new lines)", lines=5)
         | 
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                with gr.Accordion(label="Advanced Settings"):
         | 
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                    with gr.Row():
         | 
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            +
                        shared_score_shift_input = gr.Slider(value=1.5, label="shared_score_shift", minimum=1.0, maximum=2.0, step=0.05)
         | 
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            +
                        shared_score_scale_input = gr.Slider(value=0.5, label="shared_score_scale", minimum=0.0, maximum=1.0, step=0.05)
         | 
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                        guidance_scale_input = gr.Slider(value=10.0, label="guidance_scale", minimum=5.0, maximum=20.0, step=1)
         | 
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                        num_inference_steps_input = gr.Slider(value=12, label="num_inference_steps", minimum=1, maximum=12, step=1)
         | 
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            +
                        seed_input = gr.Slider(value=0, label="seed", minimum=0, maximum=1000000, step=42)
         | 
|  | |
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                with gr.Row():
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                    run_button = gr.Button("Generate Images")
         | 
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                with gr.Row():
         | 
|  | |
| 64 |  | 
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                run_button.click(
         | 
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                    run,
         | 
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            +
                    inputs=[image_input, style_input, image_desc_input, prompts_input, shared_score_shift_input, shared_score_scale_input, guidance_scale_input, num_inference_steps_input, seed_input],
         | 
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                    outputs=output_gallery
         | 
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                )
         | 
| 70 |  | 

