diff --git a/comfy/ldm/chroma/layers_dct.py b/comfy/ldm/chroma/layers_dct.py
index 0f8b81b43..24c1aa7ee 100644
--- a/comfy/ldm/chroma/layers_dct.py
+++ b/comfy/ldm/chroma/layers_dct.py
@@ -6,6 +6,7 @@ from torch import nn
 
 from comfy.ldm.flux.layers import RMSNorm
 
+
 class NerfEmbedder(nn.Module):
     """
     An embedder module that combines input features with a 2D positional
@@ -130,6 +131,7 @@ class NerfEmbedder(nn.Module):
         # No-op if already the same dtype.
         return inputs.to(dtype=orig_dtype)
 
+
 class NerfGLUBlock(nn.Module):
     """
     A NerfBlock using a Gated Linear Unit (GLU) like MLP.
@@ -182,6 +184,7 @@ class NerfFinalLayer(nn.Module):
         # So we temporarily move the channel dimension to the end for the norm operation.
         return self.linear(self.norm(x.movedim(1, -1))).movedim(-1, 1)
 
+
 class NerfFinalLayerConv(nn.Module):
     def __init__(self, hidden_size, out_channels, dtype=None, device=None, operations=None):
         super().__init__()
diff --git a/comfy/ldm/chroma/model_dct.py b/comfy/ldm/chroma/model_dct.py
index e64bbba2f..1c5e0bb3a 100644
--- a/comfy/ldm/chroma/model_dct.py
+++ b/comfy/ldm/chroma/model_dct.py
@@ -10,10 +10,7 @@ from torch import Tensor, nn
 from einops import repeat
 import comfy.ldm.common_dit
 
-from comfy.ldm.flux.layers import (
-    EmbedND,
-    timestep_embedding,
-)
+from comfy.ldm.flux.layers import EmbedND
 
 from .layers import (
     DoubleStreamBlock,
@@ -29,6 +26,7 @@ from .layers_dct import (
 
 from . import model as chroma_model
 
+
 @dataclass
 class ChromaRadianceParams(chroma_model.ChromaParams):
     patch_size: int