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from diffusers import StableDiffusionPipeline |
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import torch |
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modelieo=['nitrosocke/Arcane-Diffusion', |
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'dreamlike-art/dreamlike-diffusion-1.0', |
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'nitrosocke/archer-diffusion', |
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'Linaqruf/anything-v3.0', |
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'nitrosocke/mo-di-diffusion', |
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'nitrosocke/classic-anim-diffusion', |
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'dallinmackay/Van-Gogh-diffusion', |
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'wavymulder/wavyfusion', |
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'wavymulder/Analog-Diffusion', |
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'nitrosocke/redshift-diffusion', |
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'prompthero/midjourney-v4-diffusion', |
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'hakurei/waifu-diffusion', |
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'DGSpitzer/Cyberpunk-Anime-Diffusion', |
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'nitrosocke/elden-ring-diffusion', |
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'naclbit/trinart_stable_diffusion_v2', |
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'nitrosocke/spider-verse-diffusion', |
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'Fictiverse/Stable_Diffusion_BalloonArt_Model', |
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'dallinmackay/Tron-Legacy-diffusion', |
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'lambdalabs/sd-pokemon-diffusers', |
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'AstraliteHeart/pony-diffusion', |
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'nousr/robo-diffusion'] |
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def TextToImage(Prompt,model): |
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model_id = model |
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) |
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pipe = pipe.to("cpu") |
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prompt = Prompt |
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image = pipe(prompt).images[0] |
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return image |
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import gradio as gr |
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interface = gr.Interface(fn=TextToImage, |
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inputs=["text", gr.Dropdown(modelieo)], |
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outputs="image", |
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title='Text to Image') |
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interface.launch() |