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| import gradio as gr | |
| import torch | |
| from torch import autocast | |
| from kandinsky2 import get_kandinsky2 | |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') | |
| model = get_kandinsky2(device, task_type='text2img') | |
| def infer(prompt): | |
| images = model.generate_text2img(prompt, batch_size=4, h=512, w=512, num_steps=75, denoised_type='dynamic_threshold', dynamic_threshold_v=99.5, sampler='ddim_sampler', ddim_eta=0.05, guidance_scale=10) | |
| return images | |
| css = """ | |
| .gradio-container { | |
| font-family: 'IBM Plex Sans', sans-serif; | |
| } | |
| .gr-button { | |
| color: white; | |
| border-color: black; | |
| background: black; | |
| } | |
| input[type='range'] { | |
| accent-color: black; | |
| } | |
| .dark input[type='range'] { | |
| accent-color: #dfdfdf; | |
| } | |
| .container { | |
| max-width: 730px; | |
| margin: auto; | |
| padding-top: 1.5rem; | |
| } | |
| #gallery { | |
| min-height: 22rem; | |
| margin-bottom: 15px; | |
| margin-left: auto; | |
| margin-right: auto; | |
| border-bottom-right-radius: .5rem !important; | |
| border-bottom-left-radius: .5rem !important; | |
| } | |
| #gallery>div>.h-full { | |
| min-height: 20rem; | |
| } | |
| .details:hover { | |
| text-decoration: underline; | |
| } | |
| .gr-button { | |
| white-space: nowrap; | |
| } | |
| .gr-button:focus { | |
| border-color: rgb(147 197 253 / var(--tw-border-opacity)); | |
| outline: none; | |
| box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); | |
| --tw-border-opacity: 1; | |
| --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); | |
| --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); | |
| --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); | |
| --tw-ring-opacity: .5; | |
| } | |
| #advanced-btn { | |
| font-size: .7rem !important; | |
| line-height: 19px; | |
| margin-top: 12px; | |
| margin-bottom: 12px; | |
| padding: 2px 8px; | |
| border-radius: 14px !important; | |
| } | |
| #advanced-options { | |
| display: none; | |
| margin-bottom: 20px; | |
| } | |
| .footer { | |
| margin-bottom: 45px; | |
| margin-top: 35px; | |
| text-align: center; | |
| border-bottom: 1px solid #e5e5e5; | |
| } | |
| .footer>p { | |
| font-size: .8rem; | |
| display: inline-block; | |
| padding: 0 10px; | |
| transform: translateY(10px); | |
| background: white; | |
| } | |
| .dark .footer { | |
| border-color: #303030; | |
| } | |
| .dark .footer>p { | |
| background: #0b0f19; | |
| } | |
| .acknowledgments h4{ | |
| margin: 1.25em 0 .25em 0; | |
| font-weight: bold; | |
| font-size: 115%; | |
| } | |
| #container-advanced-btns{ | |
| display: flex; | |
| flex-wrap: wrap; | |
| justify-content: space-between; | |
| align-items: center; | |
| } | |
| .animate-spin { | |
| animation: spin 1s linear infinite; | |
| } | |
| @keyframes spin { | |
| from { | |
| transform: rotate(0deg); | |
| } | |
| to { | |
| transform: rotate(360deg); | |
| } | |
| } | |
| #share-btn-container { | |
| display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; | |
| } | |
| #share-btn { | |
| all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important; | |
| } | |
| #share-btn * { | |
| all: unset; | |
| } | |
| .gr-form{ | |
| flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0; | |
| } | |
| #prompt-container{ | |
| gap: 0; | |
| } | |
| #generated_id{ | |
| min-height: 700px | |
| } | |
| """ | |
| block = gr.Blocks(css=css) | |
| examples = [ | |
| [ | |
| 'Красная площадь' | |
| ], | |
| [ | |
| 'Thinking man in anime style' | |
| ], | |
| [ | |
| 'אבוקדו' | |
| ], | |
| ] | |
| with block as demo: | |
| gr.Markdown(""" | |
| [](https://pytorch.org/) [](https://huggingface.co/sberbank-ai/Kandinsky_2.0) | |
| ## Model architecture: | |
| It is a latent diffusion model with two multilingual text encoders: | |
| * mCLIP-XLMR 560M parameters | |
| * mT5-encoder-small 146M parameters | |
| These encoders and multilingual training datasets unveil the real multilingual text-to-image generation experience! | |
| **Kandinsky 2.0** was trained on a large 1B multilingual set, including samples that we used to train Kandinsky. | |
| In terms of diffusion architecture Kandinsky 2.0 implements UNet with 1.2B parameters. | |
| **Kandinsky 2.0** architecture overview: | |
|  | |
| """ | |
| ) | |
| with gr.Group(): | |
| with gr.Box(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| text = gr.Textbox( | |
| label="Enter your prompt", show_label=False, max_lines=1 | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| btn = gr.Button("Run").style( | |
| margin=False, | |
| rounded=(False, True, True, False), | |
| ) | |
| gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="generated_id").style( | |
| grid=[2], height="auto" | |
| ) | |
| ex = gr.Examples(examples=examples, fn=infer, inputs=[text], outputs=gallery, cache_examples=True) | |
| ex.dataset.headers = [""] | |
| text.submit(infer, inputs=[text], outputs=gallery) | |
| btn.click(infer, inputs=[text], outputs=gallery) | |
| gr.Markdown(""" | |
| # Authors | |
| + Arseniy Shakhmatov: [Github](https://github.com/cene555), [Blog](https://t.me/gradientdip) | |
| + Anton Razzhigaev: [Github](https://github.com/razzant), [Blog](https://t.me/abstractDL) | |
| + Aleksandr Nikolich: [Github](https://github.com/AlexWortega), [Blog](https://t.me/lovedeathtransformers) | |
| + Vladimir Arkhipkin: [Github](https://github.com/oriBetelgeuse) | |
| + Igor Pavlov: [Github](https://github.com/boomb0om) | |
| + Andrey Kuznetsov: [Github](https://github.com/kuznetsoffandrey) | |
| + Denis Dimitrov: [Github](https://github.com/denndimitrov) | |
| """ | |
| ) | |
| demo.queue(max_size=25).launch() | |