diff --git a/app/Dockerfile b/app/Dockerfile
index 7657b5e..3b79c54 100644
--- a/app/Dockerfile
+++ b/app/Dockerfile
@@ -5,7 +5,7 @@ RUN apt-get update \
     && apt-get autoremove -y \
     && apt-get clean -y \
     && rm -rf /var/lib/apt/lists/* \
-    && pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu117 --no-cache-dir \
+    && pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu121 --no-cache-dir \
     && mkdir -p /vol/cache/esrgan \
     && wget --progress=dot:giga https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P /vol/cache/esrgan \
     && wget --progress=dot:giga https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth -P /vol/cache/esrgan \
diff --git a/app/__main__.py b/app/__main__.py
index 48130f2..77c07c0 100644
--- a/app/__main__.py
+++ b/app/__main__.py
@@ -2,10 +2,10 @@ from __future__ import annotations
 
 import stable_diffusion_1_5
 import stable_diffusion_xl
-from setup import stub
+from setup import app
 
 
-@stub.function(gpu="A10G")
+@app.function(gpu="A10G")
 def main():
     stable_diffusion_1_5.SD15
     stable_diffusion_xl.SDXLTxt2Img
diff --git a/app/requirements.txt b/app/requirements.txt
index 7c774a5..2f53bcf 100644
--- a/app/requirements.txt
+++ b/app/requirements.txt
@@ -1,21 +1,21 @@
 invisible_watermark
 accelerate
-diffusers[torch]==0.24.0
-onnxruntime==1.16.3
-safetensors==0.4.1
-torch==2.1.0
-transformers==4.39.1
-xformers==0.0.22.post7
+diffusers[torch]==0.27.2
+onnxruntime==1.17.3
+safetensors==0.4.3
+torch==2.2.2
+transformers==4.39.3
+xformers==0.0.25.post1
 
 realesrgan==0.3.0
 basicsr>=1.4.2
 facexlib>=0.3.0
 gfpgan>=1.3.8
-scipy==1.12.0
+scipy==1.13.0
 opencv-python
 Pillow
 pillow-avif-plugin
-torchvision
+torchvision==0.17.2
 tqdm
 
 controlnet_aux
diff --git a/app/setup.py b/app/setup.py
index 8212b39..fd927f5 100644
--- a/app/setup.py
+++ b/app/setup.py
@@ -3,7 +3,7 @@ from __future__ import annotations
 import os
 
 import diffusers
-from modal import Image, Mount, Secret, Stub
+from modal import App, Image, Mount, Secret
 
 BASE_CACHE_PATH = "/vol/cache"
 BASE_CACHE_PATH_LORA = "/vol/cache/lora"
@@ -58,7 +58,7 @@ def download_model(name: str, model_url: str, token: str):
     cache_path = os.path.join(BASE_CACHE_PATH, name)
     pipe = diffusers.StableDiffusionPipeline.from_single_file(
         pretrained_model_link_or_path=model_url,
-        use_auth_token=token,
+        token=token,
         cache_dir=cache_path,
     )
     pipe.save_pretrained(cache_path, safe_serialization=True)
@@ -131,12 +131,12 @@ def build_image():
             )
 
 
-stub = Stub("stable-diffusion-cli")
+app = App("stable-diffusion-cli")
 base_stub = Image.from_dockerfile(
     path="Dockerfile",
     context_mount=Mount.from_local_file("requirements.txt"),
 )
-stub.image = base_stub.dockerfile_commands(
+app.image = base_stub.dockerfile_commands(
     "FROM base",
     "COPY config.yml /",
     context_mount=Mount.from_local_file("config.yml"),
diff --git a/app/stable_diffusion_1_5.py b/app/stable_diffusion_1_5.py
index 6c61f1d..b306714 100644
--- a/app/stable_diffusion_1_5.py
+++ b/app/stable_diffusion_1_5.py
@@ -10,11 +10,11 @@ from setup import (
     BASE_CACHE_PATH_CONTROLNET,
     BASE_CACHE_PATH_LORA,
     BASE_CACHE_PATH_TEXTUAL_INVERSION,
-    stub,
+    app,
 )
 
 
-@stub.cls(
+@app.cls(
     gpu="A10G",
     secrets=[Secret.from_dotenv(__file__)],
 )
@@ -187,15 +187,16 @@ class SD15:
             generated_images.extend(fixed_by_controlnet)
             base_images = fixed_by_controlnet
 
-        if upscaler != "":
-            upscaled = self._upscale(
-                base_images=base_images,
-                half_precision=False,
-                tile=700,
-                upscaler=upscaler,
-                use_face_enhancer=use_face_enhancer,
-            )
-            generated_images.extend(upscaled)
+        # TODO: Upscaler stopped working due to update of dependent packages. Replace with diffusers upscaler.
+        # if upscaler != "":
+        #     upscaled = self._upscale(
+        #         base_images=base_images,
+        #         half_precision=False,
+        #         tile=700,
+        #         upscaler=upscaler,
+        #         use_face_enhancer=use_face_enhancer,
+        #     )
+        #     generated_images.extend(upscaled)
 
         image_output = []
         for image in generated_images:
diff --git a/app/stable_diffusion_xl.py b/app/stable_diffusion_xl.py
index 3cc5afb..23c3b49 100644
--- a/app/stable_diffusion_xl.py
+++ b/app/stable_diffusion_xl.py
@@ -5,10 +5,10 @@ import os
 
 import PIL.Image
 from modal import Secret, enter, method
-from setup import BASE_CACHE_PATH, BASE_CACHE_PATH_CONTROLNET, stub
+from setup import BASE_CACHE_PATH, app
 
 
-@stub.cls(
+@app.cls(
     gpu="A10G",
     secrets=[Secret.from_dotenv(__file__)],
 )
@@ -39,13 +39,13 @@ class SDXLTxt2Img:
             variant="fp16",
         )
 
-        # self.refiner_cache_path = self.cache_path + "-refiner"
-        # self.refiner = diffusers.StableDiffusionXLImg2ImgPipeline.from_pretrained(
-        #     self.refiner_cache_path,
-        #     torch_dtype=torch.float16,
-        #     use_safetensors=True,
-        #     variant="fp16",
-        # )
+        self.refiner_cache_path = self.cache_path + "-refiner"
+        self.refiner = diffusers.StableDiffusionXLImg2ImgPipeline.from_pretrained(
+            self.refiner_cache_path,
+            torch_dtype=torch.float16,
+            use_safetensors=True,
+            variant="fp16",
+        )
 
         # controlnets = config.get("controlnets")
         # if controlnets is not None:
@@ -94,12 +94,10 @@ class SDXLTxt2Img:
         n_prompt: str,
         height: int = 1024,
         width: int = 1024,
-        batch_size: int = 1,
         steps: int = 30,
         seed: int = 1,
         upscaler: str = "",
         use_face_enhancer: bool = False,
-        fix_by_controlnet_tile: bool = False,
         output_format: str = "png",
     ) -> list[bytes]:
         """
@@ -119,37 +117,33 @@ class SDXLTxt2Img:
         ).images
         base_images = generated_images
 
-        # for image in base_images:
-        #     image = self._resize_image(image=image, scale_factor=2)
-        #     self.refiner.to("cuda")
-        #     refined_images = self.refiner(
-        #         prompt=prompt,
-        #         negative_prompt=n_prompt,
-        #         num_inference_steps=steps,
-        #         strength=0.1,
-        #         # guidance_scale=7.5,
-        #         generator=generator,
-        #         image=image,
-        #     ).images
-        # generated_images.extend(refined_images)
-        # base_images = refined_images
+        for image in base_images:
+            image = self._resize_image(image=image, scale_factor=2)
+            self.refiner.to("cuda")
+            refined_images = self.refiner(
+                prompt=prompt,
+                negative_prompt=n_prompt,
+                num_inference_steps=steps,
+                strength=0.1,
+                # guidance_scale=7.5,
+                generator=generator,
+                image=image,
+            ).images
+        generated_images.extend(refined_images)
+        base_images = refined_images
+
         """
         Fix the generated images by the control_v11f1e_sd15_tile when `fix_by_controlnet_tile` is `True`.
         https://huggingface.co/lllyasviel/control_v11f1e_sd15_tile
         """
         # if fix_by_controlnet_tile:
         #     max_embeddings_multiples = self._count_token(p=prompt, n=n_prompt)
-        #     print("========================確認用========================")
-        #     print("Step1")
         #     self.controlnet_pipe.to("cuda")
         #     self.controlnet_pipe.enable_vae_tiling()
         #     self.controlnet_pipe.enable_xformers_memory_efficient_attention()
-        #     print("Step2")
         #     for image in base_images:
         #         image = self._resize_image(image=image, scale_factor=2)
-        #         print("Step3")
         #         with torch.autocast("cuda"):
-        #             print("Step4")
         #             fixed_by_controlnet = self.controlnet_pipe(
         #                 prompt=prompt * batch_size,
         #                 negative_prompt=n_prompt * batch_size,
@@ -160,7 +154,6 @@ class SDXLTxt2Img:
         #                 generator=generator,
         #                 image=image,
         #             ).images
-        #     print("Step5")
         #     generated_images.extend(fixed_by_controlnet)
         #     base_images = fixed_by_controlnet
 
diff --git a/cmd/sd15_txt2img.py b/cmd/sd15_txt2img.py
index 64131f4..821bdea 100644
--- a/cmd/sd15_txt2img.py
+++ b/cmd/sd15_txt2img.py
@@ -3,11 +3,11 @@ import time
 import modal
 import util
 
-stub = modal.Stub("run-stable-diffusion-cli")
-stub.run_inference = modal.Function.from_name("stable-diffusion-cli", "SD15.run_txt2img_inference")
+app = modal.App("run-stable-diffusion-cli")
+app.run_inference = modal.Function.from_name("stable-diffusion-cli", "SD15.run_txt2img_inference")
 
 
-@stub.local_entrypoint()
+@app.local_entrypoint()
 def main(
     prompt: str,
     n_prompt: str,
@@ -33,7 +33,7 @@ def main(
         if seed == -1:
             seed_generated = util.generate_seed()
         start_time = time.time()
-        images = stub.run_inference.remote(
+        images = app.run_inference.remote(
             prompt=prompt,
             n_prompt=n_prompt,
             height=height,
diff --git a/cmd/sdxl_txt2img.py b/cmd/sdxl_txt2img.py
index 0b018a9..7a9f5f5 100644
--- a/cmd/sdxl_txt2img.py
+++ b/cmd/sdxl_txt2img.py
@@ -3,16 +3,18 @@ import time
 import modal
 import util
 
-stub = modal.Stub("run-stable-diffusion-cli")
-stub.run_inference = modal.Function.from_name("stable-diffusion-cli", "SDXLTxt2Img.run_inference")
+app = modal.Stub("run-stable-diffusion-cli")
+app.run_inference = modal.Function.from_name("stable-diffusion-cli", "SDXLTxt2Img.run_inference")
 
 
-@stub.local_entrypoint()
+@app.local_entrypoint()
 def main(
     prompt: str,
+    n_prompt: str,
     height: int = 1024,
     width: int = 1024,
     samples: int = 5,
+    steps: int = 20,
     seed: int = -1,
     upscaler: str = "",
     use_face_enhancer: str = "False",
@@ -29,10 +31,12 @@ def main(
         if seed == -1:
             seed_generated = util.generate_seed()
         start_time = time.time()
-        images = stub.run_inference.remote(
+        images = app.run_inference.remote(
             prompt=prompt,
+            n_prompt=n_prompt,
             height=height,
             width=width,
+            steps=steps,
             seed=seed_generated,
             upscaler=upscaler,
             use_face_enhancer=use_face_enhancer == "True",