diff --git a/comfy/ldm/modules/attention.py b/comfy/ldm/modules/attention.py
index 43991fd40..c18266672 100644
--- a/comfy/ldm/modules/attention.py
+++ b/comfy/ldm/modules/attention.py
@@ -45,8 +45,8 @@ try:
     AITER_ATTENTION_IS_AVAILABLE = True
 except ImportError:
     if model_management.aiter_attention_enabled():
-        logging.error(f"\n\nTo use the `--use-aiter-attention` feature, the `aiter` package must be installed first.")
-        logging.error(f"Installation instructions: https://github.com/ROCm/aiter/tree/main?tab=readme-ov-file#installation")
+        logging.error("\n\nTo use the `--use-aiter-attention` feature, the `aiter` package must be installed first.")
+        logging.error("Installation instructions: https://github.com/ROCm/aiter/tree/main?tab=readme-ov-file#installation")
         exit(-1)
 
 REGISTERED_ATTENTION_FUNCTIONS = {}
@@ -634,7 +634,7 @@ def attention_flash(q, k, v, heads, mask=None, attn_precision=None, skip_reshape
 def attention_aiter(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=False, skip_output_reshape=False, **kwargs):
     # Store original inputs for fallback
     q_orig, k_orig, v_orig, mask_orig = q, k, v, mask
-    
+
     if skip_reshape:
         b, _, _, dim_head = q.shape
         q, k, v = map(
@@ -649,7 +649,7 @@ def attention_aiter(q, k, v, heads, mask=None, attn_precision=None, skip_reshape
             (q, k, v),
         )
 
-    
+
     # Convert mask to [sq, sk] format for aiter bias
     bias = None
     if mask is not None:
@@ -685,7 +685,7 @@ def attention_aiter(q, k, v, heads, mask=None, attn_precision=None, skip_reshape
             cu_seqlens_q=None,
             cu_seqlens_kv=None,
         )
-        
+
         if skip_output_reshape:
             # output is (batch, seqlen, nheads, headdim), need (batch, nheads, seqlen, headdim)
             out = out.transpose(1, 2)
@@ -693,12 +693,12 @@ def attention_aiter(q, k, v, heads, mask=None, attn_precision=None, skip_reshape
             # reshape from (batch, seqlen, nheads, headdim) to (batch, seqlen, nheads * headdim)
             out = out.reshape(b, -1, heads * dim_head)
         return out
-        
+
     except Exception as e:
         logging.warning(f"Aiter Attention failed, falling back to pytorch attention: {e}")
         # Fallback to attention_pytorch with original inputs
-        return attention_pytorch(q_orig, k_orig, v_orig, heads, mask=mask_orig, 
-                                attn_precision=attn_precision, skip_reshape=skip_reshape, 
+        return attention_pytorch(q_orig, k_orig, v_orig, heads, mask=mask_orig,
+                                attn_precision=attn_precision, skip_reshape=skip_reshape,
                                 skip_output_reshape=skip_output_reshape, **kwargs)