Update app.py

app.py

@@ -32,17 +32,18 @@ JS = """function () {
 if torch.cuda.is_available():
     pipe = FluxPipeline.from_pretrained(model, torch_dtype=torch.bfloat16)
     pipe.load_lora_weights(hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"))
-    pipe.fuse_lora(lora_scale=0.125)
+    pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-blended-realistic-illustration", weight_name="FLUX-dev-lora-blended_realistic_illustration.safetensors")
+    pipe.fuse_lora(lora_scale=1.0)
     pipe.to(device="cuda", dtype=torch.bfloat16)
 
 # Function 
 @spaces.GPU(duration=120)
 def generate_image(
     prompt,
-    width=1024,
+    width=768,
     height=1024,
     scales=5,
-    steps=8,
+    steps=24,
     seed: int =-1,
     nums=1,
     progress=gr.Progress(track_tqdm=True)):
@@ -91,7 +92,7 @@ examples = [
 
 with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
     gr.HTML("<h1><center>Flux Labs</center></h1>")
-    gr.HTML("<p><center>Model Now:  Hyper-FLUX-8steps-LoRA<br>🙇‍♂️Frequent model changes</center></p>")
+    gr.HTML("<p><center>Model Now:  Shakker-Labs/FLUX.1-dev-LoRA-blended-realistic-illustration<br>🙇‍♂️Frequent model changes</center></p>")
     with gr.Row():
         with gr.Column(scale=4):
             img = gr.Gallery(label='flux Generated Image', columns = 1, preview=True, height=600)
@@ -105,7 +106,7 @@ with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
                     minimum=512,
                     maximum=1280,
                     step=8,
-                    value=1024,
+                    value=768,
                 )
                 height = gr.Slider(
                     label="Height",
@@ -126,7 +127,7 @@ with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
                     minimum=1,
                     maximum=100,
                     step=1,
-                    value=8,
+                    value=24,
                 )
                 seed = gr.Slider(
                     label="Seeds",