Update app.py

app.py

@@ -6,23 +6,18 @@ 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"
 
-# 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
 
@@ -71,12 +66,11 @@ def infer(
     width=1024,
     height=1024,
     guidance_scale=7.5,
-    num_inference_steps=4,
+    num_inference_steps=8,
     style="Style Zero",
     grid_size="1x1",
     progress=gr.Progress(track_tqdm=True),
 ):
-    # Apply selected style
     selected_style = next(s for s in style_list if s["name"] == style)
     styled_prompt = selected_style["prompt"].format(prompt=prompt)
     styled_negative_prompt = selected_style["negative_prompt"]
@@ -86,11 +80,9 @@ def infer(
 
     generator = torch.Generator().manual_seed(seed)
 
-    # Get grid size
     grid_size_x, grid_size_y = grid_sizes.get(grid_size, (1, 1))
     num_images = grid_size_x * grid_size_y
 
-    # Generate multiple images
     options = {
         "prompt": styled_prompt,
         "negative_prompt": styled_negative_prompt,
@@ -105,10 +97,8 @@ def infer(
     torch.cuda.empty_cache()  # Clear GPU memory
     result = pipe(**options)
 
-    # Create grid image
     grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))
 
-    # Paste images into the grid
     for i, img in enumerate(result.images[:num_images]):
         grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))
 
@@ -213,7 +203,7 @@ with gr.Blocks(css=css, theme="prithivMLmods/Minecraft-Theme") as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=4,
+                    value=8,
                 )
 
         gr.Examples(examples=examples,