Update app.py

app.py

@@ -274,7 +274,7 @@ print("Downloading LoRA for this Space (dagloop5/LoRA:LoRA2.safetensors)...")
 lora_path = hf_hub_download(repo_id="dagloop5/LoRA", filename="LoRA2.safetensors")
 # Create a descriptor object that the LTX loader expects.
 # initial strength is set to 1.0; we'll mutate `.strength` at runtime from the UI slider.
-lora_descriptor = LoraPathStrengthAndSDOps(lora_path, 0.75, LTXV_LORA_COMFY_RENAMING_MAP)
+lora_descriptor = LoraPathStrengthAndSDOps(lora_path, 1.0, LTXV_LORA_COMFY_RENAMING_MAP)
 
 print(f"LoRA: {lora_path}")
 
@@ -365,7 +365,7 @@ def on_highres_toggle(first_image, last_image, high_res):
     return gr.update(value=w), gr.update(value=h)
 
 
-@spaces.GPU(duration=200)
+@spaces.GPU(duration=80)
 @torch.inference_mode()
 def generate_video(
     first_image,
@@ -378,7 +378,7 @@ def generate_video(
     randomize_seed: bool = True,
     height: int = 1024,
     width: int = 1536,
-    lora_strength: float = 0.75,
+    lora_strength: float = 1.0,
     progress=gr.Progress(track_tqdm=True),
 ):
     try:
@@ -582,7 +582,7 @@ with gr.Blocks(title="LTX-2.3 Heretic Distilled") as demo:
                     info="Scale for the LoRA weights (0.0 = off). Set near 1.0 for full effect.",
                     minimum=0.0,
                     maximum=2.0,
-                    value=0.75,
+                    value=1.0,
                     step=0.01,
                 )