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library_name: aneforge
license: apache-2.0
base_model: google/vit-base-patch16-224
pipeline_tag: image-classification
tags:
- aneforge
- apple-neural-engine
---
# ViT-Base (patch16-224) (ANEForge)
An unmodified duplicate of [`google/vit-base-patch16-224`](https://huggingface.co/google/vit-base-patch16-224), tagged for use with
[**ANEForge**](https://github.com/sbryngelson/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
```python
# 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](https://aneforge.readthedocs.io) and the
[paper](https://arxiv.org/abs/2606.17090).
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