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README.md
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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
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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/
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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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# 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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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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> **TL;DR** performance is comparable to the original models from PyTorch implementations.
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> [!WARNING]
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> More models will be uploaded aligned with MLX improvement by the Apple team.
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