Update app.py

app.py

@@ -5,9 +5,11 @@ import random
 # import spaces #[uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
 import torch
+from PIL import Image
+
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-# model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+torch_dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32
 
 MODEL_OPTIONS = [
     ("stabilityai/sdxl-turbo", "SDXL Turbo (Быстро)"),
@@ -24,6 +26,31 @@ else:
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
+PIPELINES = {} 
+
+def load_pipelines():
+    # SDXL Turbo
+    mid = "stabilityai/sdxl-turbo"
+    pipe = DiffusionPipeline.from_pretrained(mid, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+    PIPELINES[mid] = pipe
+
+    # SD v1-4
+    mid = "CompVis/stable-diffusion-v1-4"
+    pipe = DiffusionPipeline.from_pretrained(mid, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+    PIPELINES[mid] = pipe
+
+    # Qwen-Image 
+    mid = "Qwen/Qwen-Image"
+    pipe = DiffusionPipeline.from_pretrained(mid, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+    PIPELINES[mid] = pipe
+
+# Вызываем сразу при импорте (на сборке образа и при старте Space)
+load_pipelines()
+
+
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
@@ -43,9 +70,7 @@ def infer(
 
     generator = torch.Generator().manual_seed(seed)
     
-    pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
-    pipe = pipe.to(device)
-    
+    pipe = PIPELINES[model_id]  
 
     image = pipe(
         prompt=prompt,