Update README.md

README.md

@@ -42,22 +42,6 @@ model.eval()
 embeds = model(x, is_training=False)
 ```
 
-You can also retrieve embeddings from the layer before the 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("image.png"))
-x = mx.expand_dims(x, 0)
-
-model = create_model("vit_base_patch16_224.dinov3", num_classes=0)
-model.eval()
-
-embeds = model(x, is_training=False)
-```
 
 ## Architecture