Update app.py

app.py

@@ -14,25 +14,25 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 torch.cuda.max_memory_allocated(device=device)
 
 def genie (prompt, negative_prompt, scale, steps, seed):
-        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.enable_xformers_memory_efficient_attention()
-        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, ).images
-        torch.cuda.empty_cache()
-        pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-        pipe = pipe.to(device)
-        pipe.enable_xformers_memory_efficient_attention()
-        torch.cuda.empty_cache()
-        image = pipe(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)
-#gr.Interface(fn=refiner, inputs='image', outputs='image').launch(debug=True)
+    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.enable_xformers_memory_efficient_attention()
+    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, ).images
+    torch.cuda.empty_cache()
+    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+    pipe = pipe.to(device)
+    pipe.enable_xformers_memory_efficient_attention()
+    torch.cuda.empty_cache()
+    image = pipe(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 0.9 GPU. <b>WARNING:</b> Capable of producing NSFW images.", 
+    article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)