Update app.py

app.py

@@ -1,17 +1,13 @@
 import gradio as gr
-import torch
 from diffusers import DiffusionPipeline
 
-# 设置模型和设备
-device = "cuda" if torch.cuda.is_available() else "cpu"
+# 加载模型到 CPU
 model_repo_id = "stabilityai/stable-diffusion-3.5-large"
+pipe = DiffusionPipeline.from_pretrained(model_repo_id)
+pipe.to("cpu")  # 使用 CPU
 
-# 加载模型
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch.float16 if device == "cuda" else torch.float32)
-pipe = pipe.to(device)
-
-# 推理函数，允许自定义宽度和高度
-def generate_image(prompt, width=1024, height=768, guidance_scale=7.5, num_inference_steps=50):
+# 定义图像生成函数，允许自定义宽度和高度
+def generate_image(prompt, width=1024, height=768, guidance_scale=7.5, num_inference_steps=40):
     image = pipe(
         prompt=prompt,
         width=width,
@@ -23,22 +19,21 @@ def generate_image(prompt, width=1024, height=768, guidance_scale=7.5, num_infer
 
 # 设置 Gradio 界面
 with gr.Blocks() as demo:
-    gr.Markdown(" # Stable Diffusion 3.5 - Custom Width & Height")
+    gr.Markdown(" # Stable Diffusion 3.5 - 自定义宽高比例")
     
     with gr.Row():
         prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here")
-    
-    # 允许用户设置宽度和高度
+
+    # 用户自定义宽度和高度
     width = gr.Slider(label="Width", minimum=512, maximum=1024, step=64, value=1024)
     height = gr.Slider(label="Height", minimum=512, maximum=1024, step=64, value=768)
     
     guidance_scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=15.0, step=0.1, value=7.5)
-    num_inference_steps = gr.Slider(label="Number of Inference Steps", minimum=1, maximum=100, step=1, value=50)
+    num_inference_steps = gr.Slider(label="Number of Inference Steps", minimum=1, maximum=50, step=1, value=40)
     
-    # 显示生成的图像
     output_image = gr.Image(label="Generated Image")
-    
-    # 点击按钮运行生成
+
+    # 点击按钮生成图像
     generate_btn = gr.Button("Generate")
     generate_btn.click(generate_image, inputs=[prompt, width, height, guidance_scale, num_inference_steps], outputs=output_image)