From 3b7c8c78920ffb826a9b0ed348a67e155e2269b4 Mon Sep 17 00:00:00 2001
From: yjy415 <2471352175@qq.com>
Date: Sun, 16 Aug 2026 13:25:17 +0800
Subject: [PATCH] Support MiniSupport MiniMax-H3 and HiDreamO1 loras trained
 with DiffSynth-Studio and ModelScope

---
 comfy/lora.py         | 6 ++++++
 comfy/lora_convert.py | 9 ---------
 2 files changed, 6 insertions(+), 9 deletions(-)

diff --git a/comfy/lora.py b/comfy/lora.py
index f0af526b5..aa98be152 100644
--- a/comfy/lora.py
+++ b/comfy/lora.py
@@ -381,6 +381,12 @@ def model_lora_keys_unet(model, key_map={}):
                 key_lora = k[len("diffusion_model."):-len(".weight")]
                 key_map["{}".format(key_lora)] = k
 
+    if isinstance(model, comfy.model_base.MiniMaxH3):
+        for k in sdk:
+            if k.startswith("diffusion_model.") and k.endswith(".weight"):
+                key_lora = k[len("diffusion_model."):-len(".weight")]
+                key_map[key_lora] = k
+
     return key_map
 
 
diff --git a/comfy/lora_convert.py b/comfy/lora_convert.py
index 30ec1024f..3580375f1 100644
--- a/comfy/lora_convert.py
+++ b/comfy/lora_convert.py
@@ -32,13 +32,6 @@ def convert_uso_lora(sd):
         sd_out[k_to] = tensor
     return sd_out
 
-def convert_lora_minimax_h3(sd):
-    sd_out = {}
-    for k in sd:
-        sd_out["diffusion_model.{}".format(k)] = sd[k]
-    return sd_out
-
-
 def convert_lora(sd):
     if "img_in.lora_A.weight" in sd and "single_blocks.0.norm.key_norm.scale" in sd:
         return convert_lora_bfl_control(sd)
@@ -46,6 +39,4 @@ def convert_lora(sd):
         return convert_lora_wan_fun(sd)
     if "single_blocks.37.processor.qkv_lora.up.weight" in sd and "double_blocks.18.processor.qkv_lora2.up.weight" in sd:
         return convert_uso_lora(sd)
-    if "blocks.0.attn.qkv_proj.lora_A.default.weight" in sd:
-        return convert_lora_minimax_h3(sd)
     return sd