Model Details
Full Model IDapple/mobilevit-small
Pipeline / Taskimage-classification
Librarytransformers
Downloads (all-time)2.2M
Likes89
Last Modified2/24/2025
Author / Orgapple
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-classification", model="apple/mobilevit-small")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfcoremlmobilevitimage-classificationvisiondataset:imagenet-1karxiv:2110.02178license:otherendpoints_compatibleregion:us
More Image Classification Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🖼️ Task: Image Classification
This model is designed for the Image Classification task. Explore more models for this use case.
All Image Classification Models →📊 Popularity
⬇ Downloads2.2M
❤️ Community Likes89
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.