ANEForge: Python for direct computation on the Apple Neural Engine
Paper • 2606.17090 • Published • 3
ViT-Base (patch16-224) (ANEForge)
An unmodified duplicate of google/vit-base-patch16-224, tagged for use with
ANEForge so the weights load and run directly on the
Apple Neural Engine (no CoreML). Weights are byte-identical to the source; see the original repo for
the model details. Licensed apache-2.0 from the source.
Use with ANEForge
# pip install "aneforge[models]"
import aneforge as af
vit = af.load_vit("aneforge/vit-base-patch16-224")
print(vit.classify(image)) # top-k (label, logit)
ANEForge compiles the model's graph into a single ANE program and streams the weights from this repo
via huggingface_hub. See the docs and the
paper.
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Model tree for aneforge/vit-base-patch16-224
Base model
google/vit-base-patch16-224
# Run this model on the Apple Neural Engine, without CoreML. import aneforge as af vit = af.load_vit("aneforge/vit-base-patch16-224") labels = vit.classify(image) # image: a PIL.Image; returns top-k (label, logit)