--- library_name: coreml license: other license_name: apple-ascl license_link: https://github.com/apple/ml-mobileclip/blob/main/LICENSE_weights_data datasets: - apple/DataCompDR-1B --- # MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training MobileCLIP was introduced in [MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training ](https://arxiv.org/pdf/2311.17049.pdf) (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. ![MobileCLIP Performance Figure](fig_accuracy_latency.png) ### Highlights * Our smallest variant `MobileCLIP-S0` obtains similar zero-shot performance as [OpenAI](https://arxiv.org/abs/2103.00020)'s ViT-B/16 model while being 4.8x faster and 2.8x smaller. * `MobileCLIP-S2` obtains better avg zero-shot performance than [SigLIP](https://arxiv.org/abs/2303.15343)'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](https://arxiv.org/abs/2309.17425) and [SigLIP](https://arxiv.org/abs/2303.15343) with similar architectures or even [OpenAI's ViT-L/14@336](https://arxiv.org/abs/2103.00020). ## 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](https://hf.co/pcuenq/MobileCLIP-S0) | 13 | 11.4 + 42.4 | 1.5 + 1.6 | 67.8 | 58.1 | | [MobileCLIP-S1](https://hf.co/pcuenq/MobileCLIP-S1) | 13 | 21.5 + 63.4 | 2.5 + 3.3 | 72.6 | 61.3 | | [MobileCLIP-S2](https://hf.co/pcuenq/MobileCLIP-S2) | 13 | 35.7 + 63.4 | 3.6 + 3.3 | 74.4 | 63.7 | | [MobileCLIP-B](https://hf.co/pcuenq/MobileCLIP-B) | 13 | 86.3 + 63.4 | 10.4 + 3.3 | 76.8 | 65.2 | | [MobileCLIP-B (LT)](https://hf.co/pcuenq/MobileCLIP-B-LT) | 36 | 86.3 + 63.4 | 10.4 + 3.3 | 77.2 | 65.8 | These Core ML models can be plugged-into the demo app provided in the official [MobileCLIP repo](https://github.com/apple/ml-mobileclip)