Model card for MobileCLIP2 S3 OpenCLIP These weights and model card are adapted from the original Apple model at https://huggingface.co/apple/MobileCLIP2 S3. This version uses canonical OpenCLIP configs and weight naming. MobileCLIP2 was introduced in MobileCLIP2: Improving Multi Modal Reinforced Training (TMLR August 2025 Featured ), by Fartash Faghri, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Alexander T Toshev, Oncel Tuzel, Hadi Pouransari. This repository contains the MobileCLIP2 S3 checkpoint. Highlights MobileCLIP2 S4 matches the accuracy of SigLIP SO400M/14 with 2x fewer parameters and surpasses DFN ViT L/14 at 2.5x lower latency measured on iPhone12 Pro Max. MobileCLIP S3/S4 are our new architectures trained on MobileCLIP’s training dataset, DataCompDR 1B (dashed lines). Our smallest variant MobileCLIP S0 obtains similar zero shot performance as OpenAI's ViT B/16 model while being 4.8x faster and 2.8x smaller. MobileCLIP S2 obtains 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 b…
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