Update app.py

app.py

@@ -17,6 +17,8 @@ from typing import Optional, Tuple
 import gradio as gr
 import spaces
 import torch
+import json, tempfile, shutil
+from huggingface_hub import snapshot_download
 from PIL import Image
 from peft import PeftModel
 from transformers import AutoProcessor
@@ -141,7 +143,8 @@ def _load_base_plus_lora(dtype: torch.dtype = torch.float16):
         low_cpu_mem_usage=True,
     )
     logger.info(f"Attaching LoRA adapters: {ADAPTER_ID}")
-    model = PeftModel.from_pretrained(base, ADAPTER_ID, is_trainable=False)
+    adapter_path = _get_sanitized_adapter_dir(ADAPTER_ID)
+    model = PeftModel.from_pretrained(base, adapter_path, is_trainable=False)
     model.eval()
     return model
 
@@ -200,6 +203,37 @@ def create_interface() -> gr.Blocks:
         )
     return demo
 
+def _get_sanitized_adapter_dir(adapter_id: str) -> str:
+    """
+    Download the adapter repo and remove unsupported keys from adapter_config.json
+    so PEFT can load it.
+    """
+    repo_dir = snapshot_download(adapter_id)
+    tmp_dir = tempfile.mkdtemp(prefix="peft_adapter_")
+    shutil.copytree(repo_dir, os.path.join(tmp_dir, "adapter"), dirs_exist_ok=True)
+    cfg_path = os.path.join(tmp_dir, "adapter", "adapter_config.json")
+
+    try:
+        with open(cfg_path, "r") as f:
+            cfg = json.load(f)
+    except Exception as e:
+        raise RuntimeError(f"Failed to read adapter_config.json: {e}")
+
+    # Remove keys PEFT LoraConfig doesn't recognize
+    for k in ["corda_config", "CoRDA_config"]:
+        if k in cfg:
+            cfg.pop(k)
+
+    # If DoRA wasn’t used, drop its block too
+    if str(cfg.get("use_dora", "false")).lower() in ["false", "0", "no"]:
+        if "dora_config" in cfg:
+            cfg.pop("dora_config")
+
+    with open(cfg_path, "w") as f:
+        json.dump(cfg, f, indent=2)
+
+    return os.path.join(tmp_dir, "adapter")
+
 def main():
     demo = create_interface()
     demo.launch(