format (#510)

python/mlx/optimizers.py

@@ -424,7 +424,9 @@ class Adamax(Adam):
     ):
         super().__init__(learning_rate, betas, eps)
         if not 0.0 <= eps:
-            raise ValueError(f"Epsilon value should be >=0, {self.eps} was provided instead")
+            raise ValueError(
+                f"Epsilon value should be >=0, {self.eps} was provided instead"
+            )
 
     def apply_single(
         self, gradient: mx.array, parameter: mx.array, state: OptimizerState