import gradio as gr import torch import modin.pandas as pd from diffusers import DiffusionPipeline device = "cuda" if torch.cuda.is_available() else "cpu" if torch.cuda.is_available(): PYTORCH_CUDA_ALLOC_CONF={'max_split_size_mb': 6000} torch.cuda.max_memory_allocated(device=device) torch.cuda.empty_cache() pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True) pipe.enable_xformers_memory_efficient_attention() pipe = pipe.to(device) pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True) torch.cuda.empty_cache() refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16") refiner.enable_xformers_memory_efficient_attention() refiner.enable_sequential_cpu_offload() refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True) else: pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", use_safetensors=True) pipe = pipe.to(device) pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True) refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True) refiner = refiner.to(device) refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True) def genie (prompt, negative_prompt, height, width, scale, steps, seed, prompt_2, negative_prompt_2, high_noise_frac): generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed) int_image = pipe(prompt, prompt_2=prompt_2, negative_prompt_2=negative_prompt_2, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, output_type="latent").images image = refiner(prompt=prompt, prompt_2=prompt_2, negative_prompt=negative_prompt, negative_prompt_2=negative_prompt_2, image=int_image, denoising_start=high_noise_frac).images[0] return image 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(512, 1024, 768, step=128, label='Height'), gr.Slider(512, 1024, 768, step=128, label='Width'), gr.Slider(1, 15, 10, label='Guidance Scale'), gr.Slider(25, maximum=50, value=25, step=1, label='Number of Iterations'), gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True), gr.Textbox(label='Embedded Prompt'), gr.Textbox(label='Embedded Negative Prompt'), gr.Slider(minimum=.7, maximum=.99, value=.95, step=.01, label='Refiner Denoise Start %')], outputs='image', title="Stable Diffusion XL 1.0 CPU or GPU", description="SDXL 1.0 CPU or GPU. Currently running on CPU.

WARNING: Extremely Slow. 65s/Iteration. Expect 25-50mins an image for 25-50 iterations respectively. This model is capable of producing NSFW (Softcore) images.", article = "If You Enjoyed this Demo and would like to Donate, you can send to any of these Wallets.
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