Downloads · 30 days
171
100% of all-time downloads
clip-vit-base-patch32
aneforge/clip-vit-base-patch32
clip-vit-base-patch32 is a zero-shot image classification model from aneforge. Use it for the zero-shot image classification task on the model card, and read the license before you ship it in a product. It is set up for aneforge.
An unmodified duplicate of openai/clip-vit-base-patch32, 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 orig…
All-time downloads
171
Public
Parameters
151M
1.8 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors605 MB · 99%
Parameter types
How the weights are stored.
F32151M · 100%
Base models
Model card
From the Hugging Face model README
CLIP ViT-B/32 (ANEForge)
An unmodified duplicate of openai/clip-vit-base-patch32, 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. See the original repo for license terms.
Use with ANEForge
# pip install "aneforge[models]"
import aneforge as af
clip = af.load_clip("aneforge/clip-vit-base-patch32")
print(clip.classify(image, ["a photo of a cat", "a photo of a dog"])) # image: a PIL.Image; zero-shot (label, prob)
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.
- Task
- Zero-Shot Image Classification
- Library
- aneforge
- Type
- clip
- Created
- Aug 30, 2026
- Updated
- Aug 31, 2026