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README.md

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+---
+{}
+---
+
+    ---
+    license: apache-2.0
+    tags:
+    - mlx
+    - mlx-image
+    - vision
+    - image-classification
+    datasets:
+    - imagenet-1k
+    library_name: mlx-image
+    ---
+    # regnet_y_800mf
+
+    A RegNetY-800MF image classification model. Pretrained in ImageNet by torchvision contributors (see ImageNet1K-V2 weight details https://github.com/pytorch/vision/issues/3995#new-recipe).
+
+    Disclaimer: This is a porting of the torch model weights to Apple MLX Framework.
+
+    ## How to use
+    ```bash
+    pip install mlx-image
+    ```
+
+    Here is how to use this model for image classification:
+
+    ```python
+    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 = mx.expand_dims(x, 0)
+
+    model = create_model("regnet_y_800mf")
+    model.eval()
+
+    logits = model(x)
+    ```
+
+    You can also use the embeds from layer before head:
+    ```python
+    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 = mx.expand_dims(x, 0)
+
+    # first option
+    model = create_model("regnet_y_800mf", num_classes=0)
+    model.eval()
+
+    embeds = model(x)
+
+    # second option
+    model = create_model("regnet_y_800mf")
+    model.eval()
+
+    embeds = model.get_features(x)
+    ```
+
+