diff --git a/src/refiners/foundationals/latent_diffusion/range_adapter.py b/src/refiners/foundationals/latent_diffusion/range_adapter.py
index 317c13b..ce24232 100644
--- a/src/refiners/foundationals/latent_diffusion/range_adapter.py
+++ b/src/refiners/foundationals/latent_diffusion/range_adapter.py
@@ -24,23 +24,23 @@ def compute_sinusoidal_embedding(
 class RangeEncoder(fl.Chain):
     def __init__(
         self,
-        sinuosidal_embedding_dim: int,
+        sinusoidal_embedding_dim: int,
         embedding_dim: int,
         device: Device | str | None = None,
         dtype: DType | None = None,
     ) -> None:
-        self.sinuosidal_embedding_dim = sinuosidal_embedding_dim
+        self.sinusoidal_embedding_dim = sinusoidal_embedding_dim
         self.embedding_dim = embedding_dim
         super().__init__(
             fl.Lambda(self.compute_sinuosoidal_embedding),
             fl.Converter(set_device=False, set_dtype=True),
-            fl.Linear(in_features=sinuosidal_embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
+            fl.Linear(in_features=sinusoidal_embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
             fl.SiLU(),
             fl.Linear(in_features=embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
         )
 
     def compute_sinuosoidal_embedding(self, x: Int[Tensor, "*batch 1"]) -> Float[Tensor, "*batch 1 embedding_dim"]:
-        return compute_sinusoidal_embedding(x, embedding_dim=self.sinuosidal_embedding_dim)
+        return compute_sinusoidal_embedding(x, embedding_dim=self.sinusoidal_embedding_dim)
 
 
 class RangeAdapter2d(fl.Sum, Adapter[fl.Conv2d]):
diff --git a/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py b/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py
index c2b49c8..efa4bc9 100644
--- a/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py
+++ b/src/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py
@@ -61,7 +61,7 @@ class TimestepEncoder(fl.Passthrough):
                 fl.Chain(
                     fl.UseContext(context="diffusion", key="timestep"),
                     RangeEncoder(
-                        sinuosidal_embedding_dim=320,
+                        sinusoidal_embedding_dim=320,
                         embedding_dim=self.timestep_embedding_dim,
                         device=device,
                         dtype=dtype,