this lora is not in comfyui format, use the code below to convert to comyui lora format.

import torch, os
from safetensors import safe_open
from safetensors.torch import save_file

def convert_lora_weights(lora_sd: dict[str, torch.Tensor], prefix: str) -> dict[str, torch.Tensor]:
converted_weights, lora_dims = {}, {}
for key, weight in lora_sd.items():
if not (key.startswith("diffusion_model.") or key.startswith("transformer.")): continue
base_name = key.split(".", 1)[1]
new_key = f"{prefix}{base_name}".replace(".", "_").replace("_lora_A_", ".lora_down.").replace("_lora_B_", ".lora_up.")
converted_weights[new_key] = weight
if "lora_down" in new_key:
lora_name = ".".join(new_key.split(".")[:-1])
lora_dims[lora_name] = weight.shape[0]
for lora_name, dim in lora_dims.items():
converted_weights[f"{lora_name}.alpha"] = torch.tensor(float(dim))
return converted_weights

def process_safetensor_file(input_path: str, output_path: str, prefix: str = "lora_"):
if not os.path.exists(input_path): return
loaded_tensors = {}
with safe_open(input_path, framework="pt", device="cpu") as f:
for key in f.keys(): loaded_tensors[key] = f.get_tensor(key)
converted_tensors = convert_lora_weights(loaded_tensors, prefix)
save_file(converted_tensors, output_path)

if name == "__main__":
input_path = 'path/to/original_lora'
output_path = "converted_output1.safetensors"
process_safetensor_file(input_path, output_path, prefix="lora_unet_")
if os.path.exists(output_path):
with safe_open(output_path, framework="pt", device="cpu") as f:
for key in f.keys(): print(f" - {key}: {f.get_tensor(key).shape}")

Hi! ChatGPT says: ".safetensors file is not a LoRA for Stable Diffusion or ComfyUI. It's a LoRA for a different architecture — most likely a CLIP-like multimodal model that isn't directly compatible with SD or ComfyUI."

Quality is very dependent on the seed for me.