Spaces:
Sleeping
Sleeping
File size: 3,643 Bytes
1cc659a 103e460 bec953a 7da8eca bec953a a9e4586 1d22228 8c080f9 41e0ed9 1d22228 7da8eca 57f90b6 7da8eca 1d22228 7da8eca 1d22228 7da8eca 1d22228 bec953a 7da8eca 1d22228 af846b8 1d22228 b531ddf b895ef0 bec953a 7da8eca bec953a b895ef0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
import gradio as gr
import torch
import numpy as np
import modin.pandas as pd
from PIL import Image
from diffusers import DiffusionPipeline, QwenImagePipeline #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()
def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed):
generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
if Model == "SD3":
#torch.cuda.max_memory_allocated(device=device)
torch.cuda.empty_cache()
SD3 = QwenImagePipeline.from_pretrained("Qwen/Qwen-Image", torch_dtype=torch.float16).to(device)
torch.cuda.empty_cache()
image=SD3(
prompt=Prompt,
height=height,
width=width,
negative_prompt=negative_prompt,
guidance_scale=scale,
num_images_per_prompt=1,
num_inference_steps=steps).images[0]
if Model == "FXL":
torch.cuda.empty_cache()
#torch.cuda.max_memory_allocated(device=device)
pipe = DiffusionPipeline.from_pretrained("circulus/canvers-fusionXL-v1", torch_dtype=torch.float16)
pipe.enable_xformers_memory_efficient_attention()
pipe = pipe.to(device)
torch.cuda.empty_cache()
#torch.cuda.max_memory_allocated(device=device)
int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, output_type="latent").images
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16") if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0")
pipe.enable_xformers_memory_efficient_attention()
pipe = pipe.to(device)
torch.cuda.empty_cache()
image = pipe(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.Radio(["SD3", "FXL"], value='SD3', label='Choose Model'),
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 V2.4 with Stable Diffusion 3 & Fusion XL - GPU",
description="<br><br><b/>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. <br><br>SHIB (BEP20): 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>PayPal: https://www.paypal.me/ManjushriBodhisattva <br>ETH: 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>DOGE: D9QdVPtcU1EFH8jDC8jhU9uBcSTqUiA8h6<br><br>Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True) |