diff --git a/src/mflux/models/common/lora/mapping/lora_loader.py b/src/mflux/models/common/lora/mapping/lora_loader.py
index 8b7f7d4..9632447 100644
--- a/src/mflux/models/common/lora/mapping/lora_loader.py
+++ b/src/mflux/models/common/lora/mapping/lora_loader.py
@@ -1,3 +1,4 @@
+import re
 from pathlib import Path
 from typing import Dict, Tuple
 
@@ -83,19 +84,20 @@ class LoRALoader:
             # Pattern matching logic
             for pattern, mapping_info in lora_mappings.items():
                 if "{block}" in pattern:
-                    # Extract block number from the weight key
-                    parts = weight_key.split(".")
-                    for i, part in enumerate(parts):
-                        if part.isdigit():
-                            try:
-                                test_block_idx = int(part)
-                                concrete_pattern = pattern.format(block=test_block_idx)
-                                if weight_key == concrete_pattern:
-                                    found_mapping = mapping_info
-                                    block_idx = test_block_idx
-                                    break
-                            except (ValueError, KeyError):
-                                continue
+                    # Extract block number from the weight key - try both . and _ separators
+                    # This handles both standard LoRA formats (dot-separated) and other formats (underscore-separated)
+                    # Find all numbers in the weight key
+                    numbers_in_key = re.findall(r'\d+', weight_key)
+                    for num_str in numbers_in_key:
+                        try:
+                            test_block_idx = int(num_str)
+                            concrete_pattern = pattern.format(block=test_block_idx)
+                            if weight_key == concrete_pattern:
+                                found_mapping = mapping_info
+                                block_idx = test_block_idx
+                                break
+                        except (ValueError, KeyError):
+                            continue
                     if found_mapping:
                         break
                 else:
diff --git a/src/mflux/models/qwen/weights/qwen_lora_mapping.py b/src/mflux/models/qwen/weights/qwen_lora_mapping.py
index d1a8822..1391e6c 100644
--- a/src/mflux/models/qwen/weights/qwen_lora_mapping.py
+++ b/src/mflux/models/qwen/weights/qwen_lora_mapping.py
@@ -13,13 +13,18 @@ class QwenLoRAMapping(LoRAMapping):
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.to_q.lora_up.weight",
                     "transformer.transformer_blocks.{block}.attn.to_q.lora.up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_q.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_q.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.to_q.lora_down.weight",
                     "transformer.transformer_blocks.{block}.attn.to_q.lora.down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_q.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_q.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.to_q.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_to_q.alpha",
                 ]
             ),
             LoRATarget(
@@ -27,13 +32,18 @@ class QwenLoRAMapping(LoRAMapping):
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.to_k.lora_up.weight",
                     "transformer.transformer_blocks.{block}.attn.to_k.lora.up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_k.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_k.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.to_k.lora_down.weight",
                     "transformer.transformer_blocks.{block}.attn.to_k.lora.down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_k.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_k.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.to_k.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_to_k.alpha",
                 ]
             ),
             LoRATarget(
@@ -41,13 +51,18 @@ class QwenLoRAMapping(LoRAMapping):
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.to_v.lora_up.weight",
                     "transformer.transformer_blocks.{block}.attn.to_v.lora.up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_v.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_v.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.to_v.lora_down.weight",
                     "transformer.transformer_blocks.{block}.attn.to_v.lora.down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_v.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_v.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.to_v.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_to_v.alpha",
                 ]
             ),
             LoRATarget(
@@ -55,109 +70,154 @@ class QwenLoRAMapping(LoRAMapping):
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.to_out.0.lora_up.weight",
                     "transformer.transformer_blocks.{block}.attn.to_out.0.lora.up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_out.0.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_out_0.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.to_out.0.lora_down.weight",
                     "transformer.transformer_blocks.{block}.attn.to_out.0.lora.down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_out.0.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_out_0.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.to_out.0.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_to_out_0.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.attn.add_q_proj",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.add_q_proj.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.add_q_proj.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_add_q_proj.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.add_q_proj.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.add_q_proj.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_add_q_proj.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.add_q_proj.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_add_q_proj.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.attn.add_k_proj",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.add_k_proj.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.add_k_proj.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_add_k_proj.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.add_k_proj.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.add_k_proj.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_add_k_proj.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.add_k_proj.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_add_k_proj.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.attn.add_v_proj",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.add_v_proj.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.add_v_proj.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_add_v_proj.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.add_v_proj.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.add_v_proj.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_add_v_proj.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.add_v_proj.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_add_v_proj.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.attn.to_add_out",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.attn.to_add_out.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_add_out.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_add_out.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.attn.to_add_out.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.attn.to_add_out.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_attn_to_add_out.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.attn.to_add_out.alpha",
+                    "lora_unet_transformer_blocks_{block}_attn_to_add_out.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.img_ff.mlp_in",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.img_mlp.net.0.proj.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.img_mlp.net.0.proj.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_img_mlp_net_0_proj.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.img_mlp.net.0.proj.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.img_mlp.net.0.proj.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_img_mlp_net_0_proj.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.img_mlp.net.0.proj.alpha",
+                    "lora_unet_transformer_blocks_{block}_img_mlp_net_0_proj.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.img_ff.mlp_out",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.img_mlp.net.2.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.img_mlp.net.2.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_img_mlp_net_2.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.img_mlp.net.2.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.img_mlp.net.2.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_img_mlp_net_2.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.img_mlp.net.2.alpha",
+                    "lora_unet_transformer_blocks_{block}_img_mlp_net_2.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.txt_ff.mlp_in",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.txt_mlp.net.0.proj.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.txt_mlp.net.0.proj.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_txt_mlp_net_0_proj.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.txt_mlp.net.0.proj.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.txt_mlp.net.0.proj.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_txt_mlp_net_0_proj.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.txt_mlp.net.0.proj.alpha",
+                    "lora_unet_transformer_blocks_{block}_txt_mlp_net_0_proj.alpha",
                 ]
             ),
             LoRATarget(
                 model_path="transformer_blocks.{block}.txt_ff.mlp_out",
                 possible_up_patterns=[
                     "transformer_blocks.{block}.txt_mlp.net.2.lora_up.weight",
+                    "diffusion_model.transformer_blocks.{block}.txt_mlp.net.2.lora_B.weight",
+                    "lora_unet_transformer_blocks_{block}_txt_mlp_net_2.lora_up.weight",
                 ],
                 possible_down_patterns=[
                     "transformer_blocks.{block}.txt_mlp.net.2.lora_down.weight",
+                    "diffusion_model.transformer_blocks.{block}.txt_mlp.net.2.lora_A.weight",
+                    "lora_unet_transformer_blocks_{block}_txt_mlp_net_2.lora_down.weight",
                 ],
                 possible_alpha_patterns=[
                     "transformer_blocks.{block}.txt_mlp.net.2.alpha",
+                    "lora_unet_transformer_blocks_{block}_txt_mlp_net_2.alpha",
                 ]
         ),
     ]