Update app.py

app.py

@@ -207,6 +207,15 @@ def _convert_diffusion_model_lora(raw: dict, base_shapes: dict, swap_fc1: bool)
     standard_ab = re.compile(r"^(?:diffusion_model\.)?(.+)\.(lora_[AB])\.weight$")
     standard_alpha = re.compile(r"^(?:diffusion_model\.)?(.+)\.alpha$")
 
+    # Family C: already-diffusers-native, PEFT's own serialization layout — `{module}.lora_A.<adapter>.weight`,
+    # confirmed against the debug dump's `transformer_blocks.0.*`/`token_refiner.refiner_blocks.*` shapes: no
+    # fused `qkv_proj` to split (`to_q`/`to_k`/`to_v` are already separate), no `mlp.fc1`/`fc2` to rename (already
+    # `ff.net.0.proj`/`ff.net.2`). The `<adapter>` segment is whatever adapter name the file happened to be saved
+    # under (e.g. "default") — discarded, since each file gets its own `adapter_name` here regardless. No `.alpha`
+    # keys exist in this family either (PEFT's native format keeps `lora_alpha` in a sidecar `adapter_config.json`
+    # we never fetch, not as tensors), so these fall to the same `alpha = rank` default every other module gets.
+    native_ab = re.compile(r"^(.+)\.(lora_[AB])\.\w+\.weight$")
+
     # Family B (Kohya-style): `lora_unet_blocks_N_TARGET.(lora_down|lora_up|alpha)` — covers SB and Fluid
     # Enhancer. `lora_down`/`lora_up` are the same A/B convention under a different name.
     kohya_ab = re.compile(
@@ -280,6 +289,15 @@ def _convert_diffusion_model_lora(raw: dict, base_shapes: dict, swap_fc1: bool)
         # adapter's dtype to match the wrapped base layer's.
         tensor = raw_tensor.to(torch.bfloat16)
 
+        match = native_ab.match(key)
+        if match:
+            module_base, ab = match.groups()
+            if f"{module_base}.weight" in base_shapes:
+                out[f"{LORA_KEY_PREFIX}.{module_base}.{ab}.weight"] = tensor
+            else:
+                print(f"[lora-convert] '{module_base}' isn't a real target — skipping", flush=True)
+            continue
+
         match = standard_ab.match(key)
         if match:
             raw_base, ab = match.groups()