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| title: README | |
| emoji: ⚡ | |
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| colorTo: green | |
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| # MLX Vision | |
| A community org for model weights compatible with `mlxim` powered by MLX. | |
| GitHub link: https://github.com/riccardomusmeci/mlx-image | |
| These are weights converted from timm/torchvision and ready to be used. | |
| ## How to install | |
| ``` | |
| pip install mlx-image | |
| ``` | |
| ## Models | |
| To load a model with pre-trained weights: | |
| ```python | |
| from mlxim.model import create_model | |
| # loading weights from HuggingFace (https://huggingface.co/mlx-vision/resnet18-mlxim) | |
| model = create_model("resnet18") # pretrained weights loaded from HF | |
| # loading weights from another HuggingFace model | |
| model = create_model("resnet18", weights="hf://repo_id/filename") | |
| # loading weights from local file | |
| model = create_model("resnet18", weights="path/to/resnet18/model.safetensors") | |
| ``` | |
| ## ImageNet-1K Results | |
| 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. | |
| > **TL;DR** performance is comparable to the original models from PyTorch implementations. | |