hotdog

app.py

@@ -1,64 +1,43 @@
 import gradio as gr
-# from diffusers import DiffusionPipeline
 from diffusers import AutoPipelineForText2Image
 import torch
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"
-
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
+if torch.backends.mps.is_available():
+    device = "mps"
+elif torch.cuda.is_available():
+    device = "cuda"
 else:
-    torch_dtype = torch.float32
+    device = "cpu"
+
+torch_dtype = torch.float32 if device == "cpu" else torch.float16
 
-# pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+model_repo_id = "stabilityai/sdxl-turbo"
 pipe = AutoPipelineForText2Image.from_pretrained(model_repo_id, torch_dtype=torch_dtype, variant="fp16")
 pipe = pipe.to(device)
 
 def infer(prompt):
-    # generator = torch.Generator().manual_seed(0)
     num_inference_steps = 2
     guidance_scale = 0.0
     width = 512
     height = 512
     image = pipe(
         prompt=prompt,
-        # negative_prompt=negative_prompt,
         guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
         width=width,
         height=height,
-        # generator=generator,
     ).images[0]
 
     return image
 
 
 examples = [
-    "A cinematic shot of a baby racoon wearing an intricate italian priest robe.",
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
+    "A cinematic shot of a baby racoon wearing an intricate kungfu master robe.",
+    "A cartoonish drawing of a tiger with a rainbow mane.",
+    "A realistic painting of a futuristic cityscape with flying cars.",
+    "A watercolor painting of a whimsical fairy in a mystical forest.",
 ]
 
-# prompt = gr.Text(
-#                 label="Prompt",
-#                 show_label=False,
-#                 max_lines=1,
-#                 placeholder="Enter your prompt",
-#                 container=False,
-#             )
-# run_button = gr.Button("Run", scale=0, variant="primary")
-# result = gr.Image(label="Result", show_label=False)
-# gr.on(
-#         triggers=[run_button.click, prompt.submit],
-#         fn=infer,
-#         inputs=[
-#             prompt,
-#         ],
-#         outputs=[result],
-#     )
-
 demo = gr.Interface(
     fn=infer,
     inputs=gr.Textbox(
@@ -70,7 +49,7 @@ demo = gr.Interface(
     title="Text-to-Image",
     description="Generate images from text prompts.",
     theme="compact",
-    # css=css,
+    examples=examples,
 )
 
 if __name__ == "__main__":