Rename app(16).py to app.py

app(16).py → app.py

@@ -277,7 +277,7 @@ PENDING_LORA_STATE: dict[str, torch.Tensor] | None = None
 PENDING_LORA_STATUS: str = "No LoRA state prepared yet."
 
 checkpoint_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename="ltx-2.3-22b-distilled.safetensors")
-spatial_upsampler_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename="ltx-2.3-spatial-upscaler-x2-1.0.safetensors")
+spatial_upsampler_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename="ltx-2.3-spatial-upscaler-x2-1.1.safetensors")
 gemma_root = snapshot_download(repo_id=GEMMA_REPO)
 
 # ---- Insert block (LoRA downloads) between lines 268 and 269 ----
@@ -287,8 +287,8 @@ LORA_REPO = "dagloop5/LoRA"
 print("=" * 80)
 print("Downloading LoRA adapters from dagloop5/LoRA...")
 print("=" * 80)
-pose_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="pose_enhancer.safetensors")
-general_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="ltx23__demopose_d3m0p0s3.safetensors")
+pose_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2_3_NSFW_furry_concat_v2.safetensors")
+general_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2.3_Reasoning_V1.safetensors")
 motion_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="motion_helper.safetensors")
 
 print(f"Pose LoRA: {pose_lora_path}")