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README.md

@@ -27,29 +27,38 @@ pip install mlx-image
 Here is how to use this model for image classification:
 
 ```python
+import mlx.core as mx
 from mlxim.model import create_model
 from mlxim.io import read_rgb
 from mlxim.transform import ImageNetTransform
+from mlxim.utils.imagenet import IMAGENET2012_CLASSES
 
 transform = ImageNetTransform(train=False, img_size=224)
-x = transform(read_rgb("cat.png"))
+x = transform(read_rgb("cat.jpg"))
+x = mx.array(x)
 x = mx.expand_dims(x, 0)
 
 model = create_model("efficientnet_b0")
 model.eval()
 
 logits = model(x)
+predicted_idx = mx.argmax(logits, axis=-1).item()
+predicted_class = list(IMAGENET2012_CLASSES.values())[predicted_idx]
+
+print(f"Predicted class: {predicted_class}")
 ```
 
 You can also use the embeds from layer before head:
 
 ```python
+import mlx.core as mx
 from mlxim.model import create_model
 from mlxim.io import read_rgb
 from mlxim.transform import ImageNetTransform
 
 transform = ImageNetTransform(train=False, img_size=224)
-x = transform(read_rgb("cat.png"))
+x = transform(read_rgb("cat.jpg"))
+x = mx.array(x)
 x = mx.expand_dims(x, 0)
 
 # first option