Instructions to use mlx-vision/wide_resnet50_2-mlxim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- mlx-image
How to use mlx-vision/wide_resnet50_2-mlxim with mlx-image:
from mlxim.model import create_model model = create_model(mlx-vision/wide_resnet50_2-mlxim)
- MLX
How to use mlx-vision/wide_resnet50_2-mlxim with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wide_resnet50_2-mlxim mlx-vision/wide_resnet50_2-mlxim
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
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README.md
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model = create_model("wide_resnet50_2")
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model.eval()
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embeds = model.
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```
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## Model Comparison
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model = create_model("wide_resnet50_2")
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model.eval()
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embeds = model.get_features(x)
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```
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## Model Comparison
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