Instructions to use apple/mobilevit-x-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/mobilevit-x-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="apple/mobilevit-x-small") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("apple/mobilevit-x-small", dtype="auto") - Notebooks
- Google Colab
- Kaggle
add Core ML model
Browse files
MobileViT.mlpackage/Data/com.apple.CoreML/model.mlmodel
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Binary file (176 kB). View file
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MobileViT.mlpackage/Data/com.apple.CoreML/weights/weight.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7c62a8b5bc1e0fa27fc55bef9cfc1b14aae91c8a495601893f5c3f855144add4
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size 9269824
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MobileViT.mlpackage/Manifest.json
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{
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"fileFormatVersion": "1.0.0",
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"itemInfoEntries": {
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"1A909735-009B-4FCB-B25E-DB59A4EBCADA": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Weights",
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"name": "weights",
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"path": "com.apple.CoreML/weights"
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},
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"5443F971-F40E-4AAE-BF31-6D8DA1931B54": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Specification",
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"name": "model.mlmodel",
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"path": "com.apple.CoreML/model.mlmodel"
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}
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},
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"rootModelIdentifier": "5443F971-F40E-4AAE-BF31-6D8DA1931B54"
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}
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