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",