import gradio as gr import torch import modin.pandas as pd import numpy as np from diffusers import DiffusionPipeline device = "cuda" if torch.cuda.is_available() else "cpu" if torch.cuda.is_available(): torch.cuda.max_memory_allocated(device=device) torch.cuda.empty_cache() pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True) pipe.enable_xformers_memory_efficient_attention() pipe = pipe.to(device) torch.cuda.empty_cache() else: pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True) pipe = pipe.to(device) def genie (prompt, steps, seed): generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed) int_image = pipe(prompt=prompt, generator=generator, num_inference_steps=steps, guidance_scale=0.0).images[0] return int_image gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), gr.Slider(1, maximum=5, value=2, step=1, label='Number of Iterations'), gr.Slider(minimum=0, step=1, maximum=999999999999999999, randomize=True), ], outputs='image', title="Stable Diffusion Turbo CPU or GPU", description="SDXL Turbo CPU or GPU. Currently running on CPU.

WARNING: 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.
BTC: bc1qzdm9j73mj8ucwwtsjx4x4ylyfvr6kp7svzjn84
3LWRoKYx6bCLnUrKEdnPo3FCSPQUSFDjFP
DOGE: DK6LRc4gfefdCTRk9xPD239N31jh9GjKez
SHIB (BEP20): 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891
PayPal: https://www.paypal.me/ManjushriBodhisattva
ETH: 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891
Code Monkey: Manjushri").launch(debug=True, max_threads=80)