Create app py

app py

@@ -0,0 +1,35 @@
+import gradio as gr
+import torch
+import numpy as np
+import modin.pandas as pd
+from PIL import Image
+from diffusers import DiffusionPipeline 
+from huggingface_hub import login
+import os
+
+login(token=os.environ.get('HF_KEY'))
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+torch.cuda.max_memory_allocated(device=device)
+pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+pipe = pipe.to(device)
+pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
+pipe.enable_xformers_memory_efficient_attention()
+torch.cuda.empty_cache()
+
+refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+refiner = refiner.to(device)
+refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
+refiner.enable_xformers_memory_efficient_attention()
+torch.cuda.empty_cache()
+
+def genie (prompt, negative_prompt, scale, steps, seed):
+     torch.cuda.empty_cache()
+     generator = torch.Generator(device=device).manual_seed(seed)
+     int_image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, width=768, height=768, output_type="latent").images 
+     torch.cuda.empty_cache()
+     image = refiner(prompt=prompt, image=int_image).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(1, 15, 10), gr.Slider(25, maximum=50, value=25, step=1), gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True)], outputs='image', title="Stable Diffusion XL .9 CPU", description="SDXL .9 CPU. <b>WARNING:</b> Extremely Slow. 65s/Iteration. Expect 25-50mins an image for 25-50 iterations respectively.", article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)