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apple / coreml-mobileclip
Model's Last Updated: November 19 2024
Introduction of coreml-mobileclip
Model Details of coreml-mobileclip
MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
MobileCLIP was introduced in MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training (CVPR 2024), by Pavan Kumar Anasosalu Vasu, Hadi Pouransari, Fartash Faghri, Raviteja Vemulapalli, Oncel Tuzel.
This repository contains the text and image encoders of all variants of MobileCLIP exported to Core ML. These Core ML models can be plugged-into the demo app provided in the official MobileCLIP repo
Highlights
-
Our smallest variant
MobileCLIP-S0obtains similar zero-shot performance as OpenAI 's ViT-B/16 model while being 4.8x faster and 2.8x smaller. -
MobileCLIP-S2obtains better avg zero-shot performance than SigLIP 's ViT-B/16 model while being 2.3x faster and 2.1x smaller, and trained with 3x less seen samples. -
MobileCLIP-B(LT) attains zero-shot ImageNet performance of 77.2% which is significantly better than recent works like DFN and SigLIP with similar architectures or even OpenAI's ViT-L/14@336 .
Checkpoints
| Model |
# Seen
Samples (B) |
# Params (M)
(img + txt) |
Latency (ms)
(img + txt) |
IN-1k Zero-Shot
Top-1 Acc. (%) |
Avg. Perf. (%)
on 38 datasets |
|---|---|---|---|---|---|
| MobileCLIP-S0 | 13 | 11.4 + 42.4 | 1.5 + 1.6 | 67.8 | 58.1 |
| MobileCLIP-S1 | 13 | 21.5 + 63.4 | 2.5 + 3.3 | 72.6 | 61.3 |
| MobileCLIP-S2 | 13 | 35.7 + 63.4 | 3.6 + 3.3 | 74.4 | 63.7 |
| MobileCLIP-B | 13 | 86.3 + 63.4 | 10.4 + 3.3 | 76.8 | 65.2 |
| MobileCLIP-B (LT) | 36 | 86.3 + 63.4 | 10.4 + 3.3 | 77.2 | 65.8 |
Download
Install
huggingface-cli
brew install huggingface-cli
huggingface-cli download --local-dir models apple/coreml-mobileclip
Citation
MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training . (CVPR 2024) Pavan Kumar Anasosalu Vasu, Hadi Pouransari, Fartash Faghri, Raviteja Vemulapalli, Oncel Tuzel.
@InProceedings{mobileclip2024,
author = {Pavan Kumar Anasosalu Vasu, Hadi Pouransari, Fartash Faghri, Raviteja Vemulapalli, Oncel Tuzel},
title = {MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2024},
}
Runs of apple coreml-mobileclip on huggingface.co
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More Information About coreml-mobileclip huggingface.co Model
Url of coreml-mobileclip
coreml-mobileclip huggingface.co Url
Provider of coreml-mobileclip huggingface.co
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Updated:March 01 2025
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