diff --git a/Diffusion360_nodes_diffusers.py b/Diffusion360_nodes_diffusers.py
index 7bbbae4..fee8bb5 100644
--- a/Diffusion360_nodes_diffusers.py
+++ b/Diffusion360_nodes_diffusers.py
@@ -36,7 +36,7 @@ class InputImage:
     FUNCTION = "load_image"
 
     def load_image(self, image):
-        image_path = os.path.join('custom_nodes/Diffusion360_ComfyUI/data/', image)
+        image_path = os.path.join('custom_nodes', 'Diffusion360_ComfyUI', 'data', image)
         img = node_helpers.pillow(Image.open, image_path)
 
         output_images = []
@@ -123,7 +123,7 @@ class Diffusion360LoaderText2Pano:
     CATEGORY = "Diffusion360/diffusers"
 
     def load_models(self, model_path):
-        pipe = Text2360PanoramaImagePipeline(os.path.join('models/diffusers', model_path), torch_dtype=torch.float16)
+        pipe = Text2360PanoramaImagePipeline(os.path.join('models', 'diffusers', model_path), torch_dtype=torch.float16)
         return (pipe, )
 
 
@@ -184,6 +184,7 @@ class Diffusion360LoaderImage2Pano:
     CATEGORY = "Diffusion360/diffusers"
 
     def load_models(self, model_path):
-        pipe = Image2360PanoramaImagePipeline(os.path.join('models/diffusers', model_path), torch_dtype=torch.float16)
-        mask = load_image('custom_nodes/Diffusion360_ComfyUI/data/i2p-mask.jpg')
+        pipe = Image2360PanoramaImagePipeline(os.path.join('models', 'diffusers', model_path), torch_dtype=torch.float16)
+        mask_path = os.path.join('custom_nodes', 'Diffusion360_ComfyUI', 'data', 'i2p-mask.jpg')
+        mask = load_image(mask_path)
         return (pipe, mask)
diff --git a/img2panoimg/image_to_360panorama_image_pipeline.py b/img2panoimg/image_to_360panorama_image_pipeline.py
index 1e4be24..5cc8779 100644
--- a/img2panoimg/image_to_360panorama_image_pipeline.py
+++ b/img2panoimg/image_to_360panorama_image_pipeline.py
@@ -1,6 +1,7 @@
 # Copyright © Alibaba, Inc. and its affiliates.
 import random
 from typing import Any, Dict
+import os
 
 import numpy as np
 import torch
@@ -47,10 +48,12 @@ class Image2360PanoramaImagePipeline(DiffusionPipeline):
         enable_xformers_memory_efficient_attention = kwargs.get(
             'enable_xformers_memory_efficient_attention', True)
 
-        model_id = model + '/sr-base/'
+        # model_id = model + '/sr-base/'
+        model_id = os.path.join(model, 'sr-base')
 
         # init i2p model
-        controlnet = ControlNetModel.from_pretrained(model + '/sd-i2p', torch_dtype=torch.float16)
+        # controlnet = ControlNetModel.from_pretrained(model + '/sd-i2p', torch_dtype=torch.float16)
+        controlnet = ControlNetModel.from_pretrained(os.path.join(model, 'sd-i2p'), torch_dtype=torch.float16)
 
         self.pipe = StableDiffusionImage2PanoPipeline.from_pretrained(
             model_id, controlnet=controlnet, torch_dtype=torch_dtype).to(device)
@@ -66,8 +69,11 @@ class Image2360PanoramaImagePipeline(DiffusionPipeline):
         self.pipe.enable_model_cpu_offload()
 
         # init controlnet-sr model
-        base_model_path = model + '/sr-base'
-        controlnet_path = model + '/sr-control'
+        # base_model_path = model + '/sr-base'
+        # controlnet_path = model + '/sr-control'
+        base_model_path = os.path.join(model, 'sr-base')
+        controlnet_path = os.path.join(model, 'sr-control')
+
         controlnet = ControlNetModel.from_pretrained(
             controlnet_path, torch_dtype=torch_dtype)
         self.pipe_sr = StableDiffusionControlNetImg2ImgPanoPipeline.from_pretrained(
@@ -94,7 +100,8 @@ class Image2360PanoramaImagePipeline(DiffusionPipeline):
             scale=2)
         netscale = 2
 
-        model_path = model + '/RealESRGAN_x2plus.pth'
+        # model_path = model + '/RealESRGAN_x2plus.pth'
+        model_path = os.path.join(model, 'RealESRGAN_x2plus.pth')
 
         dni_weight = None
         self.upsampler = RealESRGANer(
diff --git a/node.tar.gz b/node.tar.gz
new file mode 100644
index 0000000..d232b07
Binary files /dev/null and b/node.tar.gz differ
diff --git a/txt2panoimg/text_to_360panorama_image_pipeline.py b/txt2panoimg/text_to_360panorama_image_pipeline.py
index f113d97..924a85e 100644
--- a/txt2panoimg/text_to_360panorama_image_pipeline.py
+++ b/txt2panoimg/text_to_360panorama_image_pipeline.py
@@ -1,6 +1,7 @@
 # Copyright © Alibaba, Inc. and its affiliates.
 import random
 from typing import Any, Dict
+import os
 
 import numpy as np
 import torch
@@ -46,7 +47,8 @@ class Text2360PanoramaImagePipeline(DiffusionPipeline):
         enable_xformers_memory_efficient_attention = kwargs.get(
             'enable_xformers_memory_efficient_attention', True)
 
-        model_id = model + '/sd-base/'
+        # model_id = model + '/sd-base/'
+        model_id = os.path.join(model, 'sd-base')
 
         # init base model
         self.pipe = StableDiffusionBlendExtendPipeline.from_pretrained(
@@ -63,8 +65,11 @@ class Text2360PanoramaImagePipeline(DiffusionPipeline):
         self.pipe.enable_model_cpu_offload()
 
         # init controlnet-sr model
-        base_model_path = model + '/sr-base'
-        controlnet_path = model + '/sr-control'
+        # base_model_path = model + '/sr-base'
+        # controlnet_path = model + '/sr-control'
+        base_model_path = os.path.join(model, 'sr-base')
+        controlnet_path = os.path.join(model, 'sr-control')
+
         controlnet = ControlNetModel.from_pretrained(
             controlnet_path, torch_dtype=torch_dtype)
         self.pipe_sr = StableDiffusionControlNetImg2ImgPanoPipeline.from_pretrained(
@@ -91,7 +96,8 @@ class Text2360PanoramaImagePipeline(DiffusionPipeline):
             scale=2)
         netscale = 2
 
-        model_path = model + '/RealESRGAN_x2plus.pth'
+        # model_path = model + '/RealESRGAN_x2plus.pth'
+        model_path = os.path.join(model, 'RealESRGAN_x2plus.pth')
 
         dni_weight = None
         self.upsampler = RealESRGANer(