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@@ -16,22 +16,32 @@ GitHub link: https://github.com/riccardomusmeci/mlx-image
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  These are weights converted from timm/torchvision and ready to be used.
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  ## How to install
 
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  ```
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  pip install mlx-image
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  ```
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  ## Models
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- To create a model with weights:
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  ```python
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  from mlxim.model import create_model
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- # loading weights from mlx-vision
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- model = create_model("resnet18")
 
 
 
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  # loading weights from local file
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- model = create_model("resnet18", weights="path/to/weights.npz")
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  ```
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  > [!WARNING]
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- > More models will be uploaded aligned with MLX improvement by Apple team
 
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  These are weights converted from timm/torchvision and ready to be used.
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  ## How to install
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+
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  ```
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  pip install mlx-image
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  ```
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  ## Models
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+ To load a model with pre-trained weights:
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  ```python
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  from mlxim.model import create_model
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+ # loading weights from HuggingFace (https://huggingface.co/mlx-vision/resnet18-mlxim)
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+ model = create_model("resnet18") # pretrained weights loaded from HF
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+
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+ # loading weights from another HuggingFace model
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+ model = create_model("resnet18", weights="hf://repo_id/filename")
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  # loading weights from local file
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+ model = create_model("resnet18", weights="path/to/resnet18/model.npz")
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  ```
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+ ## **ImageNet-1K Results**
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+
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+ Go to https://github.com/riccardomusmeci/mlx-image/blob/main/results/results-imagenet-1k.csv to check every model converted and its performance on ImageNet-1K with different settings.
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+
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+ > **TL;DR** performance is comparable to the original models from PyTorch implementations.
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+
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  > [!WARNING]
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+ > More models will be uploaded aligned with MLX improvement by the Apple team.