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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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from diffusers import DiffusionPipeline |
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from huggingface_hub import login |
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import os |
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login(token=os.environ.get('HF_KEY')) |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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torch.cuda.max_memory_allocated(device=device) |
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def genie (prompt, negative_prompt, scale, steps, seed): |
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pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True) |
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pipe = pipe.to(device) |
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torch.cuda.empty_cache() |
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generator = torch.Generator(device=device).manual_seed(seed) |
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int_image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, ).images |
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torch.cuda.empty_cache() |
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pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True) |
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pipe = pipe.to(device) |
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torch.cuda.empty_cache() |
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image = pipe(prompt=prompt, image=int_image).images[0] |
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return image |
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gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), |
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gr.Textbox(label='What you Do Not want the AI to generate.'), |
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gr.Slider(1, 15, 10), gr.Slider(25, maximum=100, value=50, step=1), |
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gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True)], |
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outputs='image', |
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title="Stable Diffusion XL 0.9 GPU", |
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description="SDXL 0.9 GPU. <b>WARNING:</b> Capable of producing NSFW images.", |
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article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80) |
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