Add ModelSaveKJ

node to save a model with the prefix you want

__init__.py

@@ -105,6 +105,7 @@ NODE_CONFIG = {
     "EmptyLatentImagePresets": {"class": EmptyLatentImagePresets, "name": "Empty Latent Image Presets"},
     "EmptyLatentImageCustomPresets": {"class": EmptyLatentImageCustomPresets, "name": "Empty Latent Image Custom Presets"},
     "ModelPassThrough": {"class": ModelPassThrough, "name": "ModelPass"},
+    "ModelSaveKJ": {"class": ModelSaveKJ, "name": "Model Save KJ"},
     "SetShakkerLabsUnionControlNetType": {"class": SetShakkerLabsUnionControlNetType, "name": "Set Shakker Labs Union ControlNet Type"},
     #audioscheduler stuff
     "NormalizedAmplitudeToMask": {"class": NormalizedAmplitudeToMask},

nodes/nodes.py

@@ -2070,4 +2070,53 @@ class SetShakkerLabsUnionControlNetType:
         else:
             control_net.set_extra_arg("control_type", [])
 
-        return (control_net,)
+        return (control_net,)
+
+class ModelSaveKJ:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "model": ("MODEL",),
+                              "filename_prefix": ("STRING", {"default": "diffusion_models/ComfyUI"}),
+                              "model_key_prefix": ("STRING", {"default": "model.diffusion_model."}),
+                              },
+                "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},}
+    RETURN_TYPES = ()
+    FUNCTION = "save"
+    OUTPUT_NODE = True
+
+    CATEGORY = "advanced/model_merging"
+
+    def save(self, model, filename_prefix, model_key_prefix, prompt=None, extra_pnginfo=None):
+        from comfy.utils import save_torch_file
+        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
+    
+        output_checkpoint = f"{filename}_{counter:05}_.safetensors"
+        output_checkpoint = os.path.join(full_output_folder, output_checkpoint)
+
+        load_models = [model]
+
+        model_management.load_models_gpu(load_models, force_patch_weights=True)
+        default_prefix = "model.diffusion_model."
+
+        sd = model.model.state_dict_for_saving(None, None, None)
+
+        new_sd = {}
+        for k in sd:
+            if k.startswith(default_prefix):
+                new_key = model_key_prefix + k[len(default_prefix):]
+            else:
+                new_key = k  # In case the key doesn't start with the default prefix, keep it unchanged
+            t = sd[k]
+            if not t.is_contiguous():
+                t = t.contiguous()
+            new_sd[new_key] = t
+        print(full_output_folder)
+        if not os.path.exists(full_output_folder):
+            os.makedirs(full_output_folder)
+        save_torch_file(new_sd, os.path.join(full_output_folder, output_checkpoint))
+        return {}
+        
+