Update app.py

app.py

@@ -45,6 +45,7 @@ def download_hf_models(output_dir: Path) -> dict:
     - DiffSynth-Studio/General-Image-Encoders
     - Tongyi-MAI/Z-Image-Turbo  
     - Tongyi-MAI/Z-Image
+    - multimodalart/Z-Image-i2L
     
     Returns dict with paths to downloaded models.
     """
@@ -72,6 +73,11 @@ def download_hf_models(output_dir: Path) -> dict:
             "description": "Z-Image base model (transformer)",
             "allow_patterns": ["transformer/*.safetensors"],
         },
+        {
+            "repo_id": "multimodalart/Z-Image-i2L",
+            "description": "Z-Image-i2L (Image to LoRA model)",
+            "allow_patterns": ["*.safetensors"],
+        },
     ]
     
     downloaded_paths = {}
@@ -228,13 +234,17 @@ encoders_path = MODELS_DIR / "DiffSynth-Studio" / "General-Image-Encoders"
 siglip_file = get_model_files(encoders_path, "SigLIP2-G384/model.safetensors")
 dino_file = get_model_files(encoders_path, "DINOv3-7B/model.safetensors")
 
+# Z-Image-i2L from HuggingFace
+zimage_i2l_path = MODELS_DIR / "multimodalart" / "Z-Image-i2L"
+zimage_i2l_file = get_model_files(zimage_i2l_path, "model.safetensors")
+
 print(f"   Z-Image transformer: {len(zimage_transformer_files)} file(s)")
 print(f"   Text encoder: {len(text_encoder_files)} file(s)")
 print(f"   VAE: {len(vae_file)} file(s)")
 print(f"   Tokenizer: {tokenizer_path}")
 print(f"   SigLIP2: {len(siglip_file)} file(s)")
 print(f"   DINOv3: {len(dino_file)} file(s)")
-print(f"   Z-Image-i2L: ModelScope (auto-download)")
+print(f"   Z-Image-i2L: {len(zimage_i2l_file)} file(s)")
 
 # Validate files
 missing = []
@@ -244,6 +254,7 @@ if not vae_file: missing.append("VAE")
 if not tokenizer_path.exists(): missing.append("Tokenizer")
 if not siglip_file: missing.append("SigLIP2")
 if not dino_file: missing.append("DINOv3")
+if not zimage_i2l_file: missing.append("Z-Image-i2L")
 
 if missing:
     raise FileNotFoundError(f"Missing model files: {', '.join(missing)}")
@@ -251,18 +262,16 @@ if missing:
 # Step 5: Load pipeline
 print()
 print("🚀 Step 5: Loading Z-Image pipeline...")
-print("   HuggingFace models: loaded from local paths")
-print("   Z-Image-i2L: loading from ModelScope...")
+print("   All models loaded from HuggingFace local paths")
 
 model_configs = [
-    # HuggingFace models - use path= for local files
+    # All models from HuggingFace - use path= for local files
     ModelConfig(path=zimage_transformer_files, **vram_config),
     ModelConfig(path=text_encoder_files),
     ModelConfig(path=vae_file),
     ModelConfig(path=siglip_file),
     ModelConfig(path=dino_file),
-    # ModelScope only - use model_id= for remote download
-    ModelConfig(model_id="DiffSynth-Studio/Z-Image-i2L", origin_file_pattern="model.safetensors"),
+    ModelConfig(path=zimage_i2l_file),
 ]
 
 pipe = ZImagePipeline.from_pretrained(
@@ -454,7 +463,7 @@ def create_demo():
         
         gr.Markdown("""
         ---
-        **Resources:** [Z-Image-i2L](https://modelscope.cn/models/DiffSynth-Studio/Z-Image-i2L) | 
+        **Resources:** [Z-Image-i2L (HuggingFace)](https://huggingface.co/multimodalart/Z-Image-i2L) | 
         [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) |
         **Settings:** CFG=4, Sigma Shift=8, Steps=50
         """)