Update app.py

app.py

@@ -6,17 +6,23 @@ from diffusers import DiffusionPipeline
 import torch
 from PIL import Image
 
+# Device configuration
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model_repo_id = "stabilityai/stable-diffusion-3.5-large-turbo"
 
-if torch.cuda.is_available():
-    torch_dtype = torch.bfloat16
-else:
-    torch_dtype = torch.float32
+# Set data type based on device availability
+torch_dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32
 
+# Load the pipeline
 pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
 pipe = pipe.to(device)
 
+# Load LoRA weights
+pipe.load_lora_weights("prithivMLmods/SD3.5-4Step-Large-Turbo-HyperRealistic-LoRA", weight_name="SD3.5-4Step-Large-Turbo-HyperRealistic-LoRA.safetensors")
+trigger_word = "hyper realistic"  # Specify trigger word for LoRA
+pipe.fuse_lora(lora_scale=1.0)
+
+# Constants
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
@@ -93,7 +99,7 @@ def infer(
         "width": width,
         "height": height,
         "generator": generator,
-        "num_images_per_prompt": num_images,  # Ensure multiple images are generated
+        "num_images_per_prompt": num_images,
     }
 
     torch.cuda.empty_cache()  # Clear GPU memory