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import gradio as gr |
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import torch |
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import numpy as np |
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import modin.pandas as pd |
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from PIL import Image |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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from diffusers import DiffusionPipeline |
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pipe = DiffusionPipeline.from_pretrained("prompthero/openjourney-v2", safety_checker=None) |
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pipe = pipe.to(device) |
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def genie (prompt, negative_prompt, scale, steps, seed): |
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generator = torch.Generator(device=device).manual_seed(seed) |
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images = pipe(prompt, negative_prompt=negative_prompt, width=768, height=768, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator).images[0] |
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return images |
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gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), gr.Textbox(label='What you Do Not want the AI to generate.'), gr.Slider(1, 25, 10), gr.Slider(1, maximum=20, value=10, step=1), gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True)], outputs='image', title="Stable Diffusion 2.1 CPU", description="SD 2.1 CPU. <b>WARNING:</b> Extremely Slow. 130s/Iteration. Expect 14-28mins an image for 10-20 iterations respectively.", article = "Code Monkey: <a href=\"https://huggingface.co./Manjushri\">Manjushri</a>").launch(debug=True, max_threads=True) |