---
library_name: aneforge
pipeline_tag: image-classification
tags:
- apple-neural-engine
- ane
- coreml-free
- on-device
- apple-silicon
- vit
- vision-transformer
- image-classification
license: mit
---

# Image classification on the Apple Neural Engine (via ANEForge)

[ANEForge](https://github.com/sbryngelson/ANEForge) runs computation on the Apple Neural
Engine (ANE) directly, without CoreML. `load_vit` loads a Hugging Face Vision Transformer
image classifier (`ViTForImageClassification`) from the Hub by repo id and runs the whole
forward pass on the engine.

This is a usage card, not a re-hosted model: it points at the upstream weights and shows how
to run them on the ANE.

## Install

```sh
pip install aneforge
```

Apple Silicon, macOS 14+.

## Use

```python
from aneforge.models import load_vit
from PIL import Image

vit = load_vit("google/vit-base-patch16-224")   # any HF ViT image classifier
image = Image.open("cat.jpg")
print(vit.classify(image, top_k=5))              # [(label, logit), ...]; forward on the ANE
# vit(image) -> raw logits [1, num_labels]
```

## Measured

On an M5 Pro, `google/vit-base-patch16-224` runs the full forward in **~27 ms/image**, matching
the Hugging Face reference (same top-1, relerr 4e-3). Preprocessing uses the model's own
`AutoImageProcessor`.

## Scope

ViT-family classifiers with a CLS token and a pre-norm encoder (`ViTForImageClassification` and
compatible DeiT/BEiT-style models); both the modern and legacy HF weight namings are handled.
ResNet / ConvNeXt loaders are tracked as follow-up issues in the repo.

## Why the ANE

The ANE is the fixed-function accelerator on every recent Apple device. In production it is
reachable only through CoreML, which can silently fall back to CPU/GPU; ANEForge compiles the
classifier to a single ANE program and dispatches it through the same daemon and kernel-driver
stack Apple's own frameworks use.

## Links

- Code: https://github.com/sbryngelson/ANEForge
- Package: https://pypi.org/project/aneforge/
- Paper: https://arxiv.org/abs/2606.17090

## Cite

> Bryngelson, S. H. *ANEForge: Python for direct computation on the Apple Neural Engine.* arXiv:2606.17090 (2026).