feat: add new app

app.py

@@ -6,18 +6,10 @@
 @Project : Faice_text2face
 """
 import gradio as gr
-import spaces
 
 from stable_diffusion_inference import inference, MAX_SEED, MAX_IMAGE_SIZE
 from utils import timer
 
-
-@spaces.GPU(duration=65)
-def text2face(prompt):
-    image, seed = inference(prompt)
-    return image, seed
-
-
 examples = [
     "Portrait of a young woman with long wavy hair, soft studio lighting, high contrast, 4k resolution, professional headshot",
     "Close-up of a smiling man with sharp jawline, cinematic lighting, shallow depth of field, bokeh background",
@@ -69,10 +61,11 @@ h1 {
 
 with gr.Blocks(theme="apriel", css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # TensorArt Stable Diffusion 3.5 Large TurboX")
-        gr.Markdown(
-            "[8-step distilled turbo model](https://huggingface.co/tensorart/stable-diffusion-3.5-large"
-            "-TurboX)")
+        gr.Markdown(" # Fiace")
+        gr.Markdown(" ## Text2Face: Human Faces Generation with Diffusion Models")
+        # gr.Markdown(
+        #     "[8-step distilled turbo model](https://huggingface.co/tensorart/stable-diffusion-3.5-large"
+        #     "-TurboX)")
         with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
@@ -137,11 +130,11 @@ with gr.Blocks(theme="apriel", css=css) as demo:
                     value=8,
                 )
 
-        gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=text2face,
+        gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=inference,
                     cache_examples=True, cache_mode="lazy")
     gr.on(
         triggers=[run_button.click, prompt.submit],
-        fn=text2face,
+        fn=inference,
         inputs=[
             prompt,
             negative_prompt,
@@ -158,4 +151,4 @@ with gr.Blocks(theme="apriel", css=css) as demo:
 if __name__ == "__main__":
     with timer("All tasks"):
         # demo.launch(mcp_server=True)
-        demo.launch()
+        demo.launch(share=True)

stable_diffusion_inference.py

@@ -11,6 +11,7 @@ import numpy as np
 from diffusers import StableDiffusionPipeline
 from accelerate import Accelerator
 import gradio as gr
+import spaces
 
 from loguru import logger
 
@@ -42,6 +43,7 @@ MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 256
 
 
+@spaces.GPU(duration=65)
 def inference(prompt,
               negative_prompt="",
               seed=42,