diff --git a/api/onnx_web/convert/diffusion/checkpoint.py b/api/onnx_web/convert/diffusion/checkpoint.py
index ee2731a1..a486d3f9 100644
--- a/api/onnx_web/convert/diffusion/checkpoint.py
+++ b/api/onnx_web/convert/diffusion/checkpoint.py
@@ -178,7 +178,7 @@ class TrainingConfig:
     ):
         model_name = sanitize_name(model_name)
         model_dir = os.path.join(conversion.cache_path, model_name)
-        working_dir = os.path.join(model_dir, "working")
+        working_dir = f"{model_dir}-torch"
 
         if not os.path.exists(working_dir):
             os.makedirs(working_dir)
@@ -1688,33 +1688,33 @@ def extract_checkpoint(
 def convert_extract_checkpoint(
     conversion: ConversionContext,
     source: str,
-    dest: str,
+    name: str,
     is_inpainting: Optional[bool] = False,
     config_file: Optional[str] = None,
     vae_file: Optional[str] = None,
 ) -> Tuple[bool, str]:
-    working_name = os.path.join(conversion.cache_path, dest, "working")
-    model_index = os.path.join(working_name, "model_index.json")
+    dest_name = os.path.join(conversion.cache_path, f"{name}-torch")
+    model_index = os.path.join(dest_name, "model_index.json")
 
-    if os.path.exists(working_name) and os.path.exists(model_index):
-        logger.info("extracted Torch model already exists, reusing: %s", working_name)
+    if os.path.exists(dest_name) and os.path.exists(model_index):
+        logger.info("extracted Torch model already exists, reusing: %s", dest_name)
     else:
         logger.info(
             "extracting checkpoint to Torch model: %s -> %s",
             source,
-            dest,
+            name,
         )
         if extract_checkpoint(
             conversion,
-            dest,
+            name,
             source,
             config_file=config_file,
             is_inpainting=is_inpainting,
             vae_file=vae_file,
         ):
-            logger.info("extracted checkpoint to Torch model: %s", working_name)
+            logger.info("extracted checkpoint to Torch model: %s", dest_name)
         else:
             logger.error("unable to convert checkpoint to Torch model")
             raise ValueError("unable to convert checkpoint to Torch model")
 
-    return working_name
+    return dest_name
diff --git a/api/onnx_web/convert/diffusion/diffusion.py b/api/onnx_web/convert/diffusion/diffusion.py
index 303bb8e6..214d3de5 100644
--- a/api/onnx_web/convert/diffusion/diffusion.py
+++ b/api/onnx_web/convert/diffusion/diffusion.py
@@ -389,8 +389,6 @@ def convert_diffusion_diffusers(
             return (False, dest_path)
 
     cache_path = fetch_model(conversion, name, source, format=format)
-    temp_path = path.join(conversion.cache_path, f"{name}-torch")
-
     pipe_class = CONVERT_PIPELINES.get(pipe_type)
     v2, pipe_args = get_model_version(
         cache_path, conversion.map_location, size=image_size, version=version
@@ -419,7 +417,7 @@ def convert_diffusion_diffusers(
                 torch_source = convert_extract_checkpoint(
                     conversion,
                     cache_path,
-                    temp_path,
+                    name,
                     is_inpainting=is_inpainting,
                     config_file=config_path,
                     vae_file=replace_vae,