diff --git a/CHANGELOG.md b/CHANGELOG.md
index b8d2dbaf5..859c6bb25 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -142,8 +142,8 @@ As of this release, default backend is set to **diffusers** as its more feature
     download&load via network -> models -> reference -> **SegMoE SD 4x2** (3.7GB), **SegMoE XL 2x1** (10GB), **SegMoE XL 4x2**  
   - note: since segmoe is basically sequential mix of unets from multiple models, it can get large  
     SD 4x2 is ~4GB, XL 2x1 is ~10GB and XL 4x2 is 18GB  
+  - supports lora, thanks @AI-Casanova
   - support for create and load custom mixes will be added in the future  
-  - support for lora and other advanced features will be added in the future  
 - [Mixture Tiling](https://arxiv.org/abs/2302.02412)  
   - uses multiple prompts to guide different parts of the grid during diffusion process  
   - can be used ot create complex scenes with multiple subjects  
diff --git a/extensions-builtin/Lora/lora_convert.py b/extensions-builtin/Lora/lora_convert.py
index 04eb7bf84..c9d5c6a98 100644
--- a/extensions-builtin/Lora/lora_convert.py
+++ b/extensions-builtin/Lora/lora_convert.py
@@ -160,8 +160,8 @@ class KeyConvert:
                     key.append(expert_key)
                     sd_module.append(expert_module)
                     i += 1
-        # SegMoe end
-        return [key], [sd_module]
+        # SegMoE end
+        return key, sd_module
 
     def diffusers(self, key):
         if self.is_sdxl:
@@ -193,7 +193,7 @@ class KeyConvert:
                     key.append(expert_key)
                     sd_module.append(expert_module)
                     i += 1
-        # SegMoe end
+        # SegMoE end
         if debug and sd_module is None:
             raise RuntimeError(f"LoRA key not found in network_layer_mapping: key={key} mapping={shared.sd_model.network_layer_mapping.keys()}")
         return key, sd_module
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 37a9ccab5..d918f4f7c 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -583,15 +583,15 @@ def detect_pipeline(f: str, op: str = 'model', warning=True):
                     warn(f'Model detected as LCM model, but attempting to load using backend=original: {op}={f} size={size} MB')
                 guess = 'Latent Consistency Model'
             """
-            if 'instaflow' in f:
+            if 'instaflow' in f.lower():
                 if shared.backend == shared.Backend.ORIGINAL:
                     warn(f'Model detected as InstaFlow model, but attempting to load using backend=original: {op}={f} size={size} MB')
                 guess = 'InstaFlow'
-            if 'SegMoE' in f:
+            if 'segmoe' in f.lower():
                 if shared.backend == shared.Backend.ORIGINAL:
                     warn(f'Model detected as SegMoE model, but attempting to load using backend=original: {op}={f} size={size} MB')
                 guess = 'SegMoE'
-            if 'PixArt' in f:
+            if 'pixart' in f.lower():
                 if shared.backend == shared.Backend.ORIGINAL:
                     warn(f'Model detected as PixArt Alpha model, but attempting to load using backend=original: {op}={f} size={size} MB')
                 guess = 'PixArt Alpha'