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Running
on
Zero
import comfy_extras.nodes_model_merging | |
class ModelMergeSD1(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["time_embed."] = argument | |
arg_dict["label_emb."] = argument | |
for i in range(12): | |
arg_dict["input_blocks.{}.".format(i)] = argument | |
for i in range(3): | |
arg_dict["middle_block.{}.".format(i)] = argument | |
for i in range(12): | |
arg_dict["output_blocks.{}.".format(i)] = argument | |
arg_dict["out."] = argument | |
return {"required": arg_dict} | |
class ModelMergeSDXL(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["time_embed."] = argument | |
arg_dict["label_emb."] = argument | |
for i in range(9): | |
arg_dict["input_blocks.{}".format(i)] = argument | |
for i in range(3): | |
arg_dict["middle_block.{}".format(i)] = argument | |
for i in range(9): | |
arg_dict["output_blocks.{}".format(i)] = argument | |
arg_dict["out."] = argument | |
return {"required": arg_dict} | |
class ModelMergeSD3_2B(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["pos_embed."] = argument | |
arg_dict["x_embedder."] = argument | |
arg_dict["context_embedder."] = argument | |
arg_dict["y_embedder."] = argument | |
arg_dict["t_embedder."] = argument | |
for i in range(24): | |
arg_dict["joint_blocks.{}.".format(i)] = argument | |
arg_dict["final_layer."] = argument | |
return {"required": arg_dict} | |
class ModelMergeAuraflow(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["init_x_linear."] = argument | |
arg_dict["positional_encoding"] = argument | |
arg_dict["cond_seq_linear."] = argument | |
arg_dict["register_tokens"] = argument | |
arg_dict["t_embedder."] = argument | |
for i in range(4): | |
arg_dict["double_layers.{}.".format(i)] = argument | |
for i in range(32): | |
arg_dict["single_layers.{}.".format(i)] = argument | |
arg_dict["modF."] = argument | |
arg_dict["final_linear."] = argument | |
return {"required": arg_dict} | |
class ModelMergeFlux1(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["img_in."] = argument | |
arg_dict["time_in."] = argument | |
arg_dict["guidance_in"] = argument | |
arg_dict["vector_in."] = argument | |
arg_dict["txt_in."] = argument | |
for i in range(19): | |
arg_dict["double_blocks.{}.".format(i)] = argument | |
for i in range(38): | |
arg_dict["single_blocks.{}.".format(i)] = argument | |
arg_dict["final_layer."] = argument | |
return {"required": arg_dict} | |
class ModelMergeSD35_Large(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["pos_embed."] = argument | |
arg_dict["x_embedder."] = argument | |
arg_dict["context_embedder."] = argument | |
arg_dict["y_embedder."] = argument | |
arg_dict["t_embedder."] = argument | |
for i in range(38): | |
arg_dict["joint_blocks.{}.".format(i)] = argument | |
arg_dict["final_layer."] = argument | |
return {"required": arg_dict} | |
class ModelMergeMochiPreview(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["pos_frequencies."] = argument | |
arg_dict["t_embedder."] = argument | |
arg_dict["t5_y_embedder."] = argument | |
arg_dict["t5_yproj."] = argument | |
for i in range(48): | |
arg_dict["blocks.{}.".format(i)] = argument | |
arg_dict["final_layer."] = argument | |
return {"required": arg_dict} | |
class ModelMergeLTXV(comfy_extras.nodes_model_merging.ModelMergeBlocks): | |
CATEGORY = "advanced/model_merging/model_specific" | |
def INPUT_TYPES(s): | |
arg_dict = { "model1": ("MODEL",), | |
"model2": ("MODEL",)} | |
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}) | |
arg_dict["patchify_proj."] = argument | |
arg_dict["adaln_single."] = argument | |
arg_dict["caption_projection."] = argument | |
for i in range(28): | |
arg_dict["transformer_blocks.{}.".format(i)] = argument | |
arg_dict["scale_shift_table"] = argument | |
arg_dict["proj_out."] = argument | |
return {"required": arg_dict} | |
NODE_CLASS_MAPPINGS = { | |
"ModelMergeSD1": ModelMergeSD1, | |
"ModelMergeSD2": ModelMergeSD1, #SD1 and SD2 have the same blocks | |
"ModelMergeSDXL": ModelMergeSDXL, | |
"ModelMergeSD3_2B": ModelMergeSD3_2B, | |
"ModelMergeAuraflow": ModelMergeAuraflow, | |
"ModelMergeFlux1": ModelMergeFlux1, | |
"ModelMergeSD35_Large": ModelMergeSD35_Large, | |
"ModelMergeMochiPreview": ModelMergeMochiPreview, | |
"ModelMergeLTXV": ModelMergeLTXV, | |
} | |