Update app.py

app.py

@@ -3,9 +3,9 @@ import numpy as np
 import torch
 import spaces
 from diffusers import FluxPipeline, FluxTransformer2DModel
+from diffusers.utils import export_to_gif
 from huggingface_hub import hf_hub_download
 from PIL import Image
-from diffusers.utils import export_to_gif
 import uuid
 import random
 
@@ -30,9 +30,6 @@ def split_image(input_image, num_splits=4):
     return output_images
 
 pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch_dtype)
-#pipe.load_lora_weights(hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-16steps-lora.safetensors"))
-#pipe.fuse_lora(lora_scale=0.125)
-#pipe.to(device=device, dtype=torch_dtype)
 
 MAX_SEED = np.iinfo(np.int32).max
 
@@ -52,13 +49,16 @@ def infer(prompt, seed=1, randomize_seed=False, num_inference_steps=28, progress
         height=320,
         width=1280
     ).images[0]
+    
     gif_name = f"{uuid.uuid4().hex}-flux.gif"
+    
     export_to_gif(split_image(image, 4), gif_name, fps=4)
+    
     return gif_name, image, seed
 
 examples = [
-    "a cute cat raising holding a sign that reads \"Flux does Video?\"",
-    "Will Smith eating pizza",
+    "a cute cat raising a sign that reads \"Flux does Video?\"",
+    "Chris Rock eating pizza",
     "A flying saucer over the white house",
 ]