import gradio as gr import torch import numpy as np import modin.pandas as pd from PIL import Image from diffusers import DiffusionPipeline, StableDiffusion3Pipeline from huggingface_hub import hf_hub_download device = 'cuda' if torch.cuda.is_available() else 'cpu' torch.cuda.max_memory_allocated(device=device) torch.cuda.empty_cache() #torch.cuda.max_memory_allocated(device=device) pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16).to(device) pipe.enable_xformers_memory_efficient_attention() torch.cuda.empty_cache() #torch.cuda.max_memory_allocated(device=device) refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16").to(device) refiner.enable_xformers_memory_efficient_attention() torch.cuda.empty_cache() def genie (Prompt, negative_prompt, height, width, scale, steps, seed): #generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed) generator=np.random.seed(0) int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, output_type="latent").images image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=.99).images[0] torch.cuda.empty_cache() 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. 77 Token Limit'), gr.Slider(512, 1536, 1024, step=128, label='Height'), gr.Slider(512, 1536, 1024, step=128, label='Width'), gr.Slider(.5, maximum=15, value=7, step=.25, label='Guidance Scale'), gr.Slider(10, maximum=50, value=25, step=5, label='Number of Prior Iterations'), gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random')], outputs=gr.Image(label='Generated Image'), title="Manju Dream Booth V2.5 with Fusion XL - GPU", description="

Warning: This Demo is capable of producing NSFW content.", article = "If You Enjoyed this Demo and would like to Donate, you can send any amount to any of these Wallets.

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Code Monkey: Manjushri").launch(debug=True)