diff --git a/comfy/ldm/modules/diffusionmodules/model.py b/comfy/ldm/modules/diffusionmodules/model.py
index a60ca307b..ccdee1886 100644
--- a/comfy/ldm/modules/diffusionmodules/model.py
+++ b/comfy/ldm/modules/diffusionmodules/model.py
@@ -218,7 +218,7 @@ def xformers_attention(q, k, v):
     try:
         out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None)
         out = out.transpose(1, 2).reshape(B, C, H, W)
-    except NotImplementedError as e:
+    except NotImplementedError:
         out = slice_attention(q.view(B, -1, C), k.view(B, -1, C).transpose(1, 2), v.view(B, -1, C).transpose(1, 2)).reshape(B, C, H, W)
     return out
 
@@ -233,7 +233,7 @@ def pytorch_attention(q, k, v):
     try:
         out = torch.nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=None, dropout_p=0.0, is_causal=False)
         out = out.transpose(2, 3).reshape(B, C, H, W)
-    except model_management.OOM_EXCEPTION as e:
+    except model_management.OOM_EXCEPTION:
         logging.warning("scaled_dot_product_attention OOMed: switched to slice attention")
         out = slice_attention(q.view(B, -1, C), k.view(B, -1, C).transpose(1, 2), v.view(B, -1, C).transpose(1, 2)).reshape(B, C, H, W)
     return out
diff --git a/comfy/sd.py b/comfy/sd.py
index ebae7f996..88024a271 100644
--- a/comfy/sd.py
+++ b/comfy/sd.py
@@ -435,7 +435,7 @@ class VAE:
                 if pixel_samples is None:
                     pixel_samples = torch.empty((samples_in.shape[0],) + tuple(out.shape[1:]), device=self.output_device)
                 pixel_samples[x:x+batch_number] = out
-        except model_management.OOM_EXCEPTION as e:
+        except model_management.OOM_EXCEPTION:
             logging.warning("Warning: Ran out of memory when regular VAE decoding, retrying with tiled VAE decoding.")
             dims = samples_in.ndim - 2
             if dims == 1:
@@ -490,7 +490,7 @@ class VAE:
                     samples = torch.empty((pixel_samples.shape[0],) + tuple(out.shape[1:]), device=self.output_device)
                 samples[x:x + batch_number] = out
 
-        except model_management.OOM_EXCEPTION as e:
+        except model_management.OOM_EXCEPTION:
             logging.warning("Warning: Ran out of memory when regular VAE encoding, retrying with tiled VAE encoding.")
             if len(pixel_samples.shape) == 3:
                 samples = self.encode_tiled_1d(pixel_samples)
diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py
index a454f3bb3..a9de659bd 100644
--- a/comfy/sd1_clip.py
+++ b/comfy/sd1_clip.py
@@ -382,7 +382,7 @@ def load_embed(embedding_name, embedding_directory, embedding_size, embed_key=No
                     embed_out = safe_load_embed_zip(embed_path)
             else:
                 embed = torch.load(embed_path, map_location="cpu")
-    except Exception as e:
+    except Exception:
         logging.warning("{}\n\nerror loading embedding, skipping loading: {}".format(traceback.format_exc(), embedding_name))
         return None
 
diff --git a/fix_torch.py b/fix_torch.py
index 4aecb23f0..25fabe211 100644
--- a/fix_torch.py
+++ b/fix_torch.py
@@ -23,6 +23,6 @@ def fix_pytorch_libomp():
                 break
         try:
             mydll = ctypes.cdll.LoadLibrary(test_file)
-        except FileNotFoundError as e:
+        except FileNotFoundError:
             logging.warning("Detected pytorch version with libomp issue, patching.")
             shutil.copyfile(os.path.join(lib_folder, "libiomp5md.dll"), dest)
diff --git a/server.py b/server.py
index 5e86558d4..7345d0f2a 100644
--- a/server.py
+++ b/server.py
@@ -561,7 +561,7 @@ class PromptServer():
                 for x in nodes.NODE_CLASS_MAPPINGS:
                     try:
                         out[x] = node_info(x)
-                    except Exception as e:
+                    except Exception:
                         logging.error(f"[ERROR] An error occurred while retrieving information for the '{x}' node.")
                         logging.error(traceback.format_exc())
                 return web.json_response(out)
@@ -829,7 +829,7 @@ class PromptServer():
         for handler in self.on_prompt_handlers:
             try:
                 json_data = handler(json_data)
-            except Exception as e:
+            except Exception:
                 logging.warning(f"[ERROR] An error occurred during the on_prompt_handler processing")
                 logging.warning(traceback.format_exc())