diff --git a/src/diffusers/models/resnet.py b/src/diffusers/models/resnet.py
index 49ff7d6bfa..6b0089d5c2 100644
--- a/src/diffusers/models/resnet.py
+++ b/src/diffusers/models/resnet.py
@@ -335,8 +335,6 @@ class ResnetBlock2D(nn.Module):
     def forward(self, x, temb):
         hidden_states = x
 
-        # make sure hidden states is in float32
-        # when running in half-precision
         hidden_states = self.norm1(hidden_states)
         hidden_states = self.nonlinearity(hidden_states)
 
@@ -353,8 +351,6 @@ class ResnetBlock2D(nn.Module):
             temb = self.time_emb_proj(self.nonlinearity(temb))[:, :, None, None]
             hidden_states = hidden_states + temb
 
-        # make sure hidden states is in float32
-        # when running in half-precision
         hidden_states = self.norm2(hidden_states)
         hidden_states = self.nonlinearity(hidden_states)
 
diff --git a/src/diffusers/models/unet_2d_condition.py b/src/diffusers/models/unet_2d_condition.py
index 04453e0645..dd9e2e570b 100644
--- a/src/diffusers/models/unet_2d_condition.py
+++ b/src/diffusers/models/unet_2d_condition.py
@@ -313,8 +313,6 @@ class UNet2DConditionModel(ModelMixin, ConfigMixin):
                     hidden_states=sample, temb=emb, res_hidden_states_tuple=res_samples, upsample_size=upsample_size
                 )
         # 6. post-process
-        # make sure hidden states is in float32
-        # when running in half-precision
         sample = self.conv_norm_out(sample)
         sample = self.conv_act(sample)
         sample = self.conv_out(sample)