apple / mobileclip_b_lt_timm

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Total runs: 36
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7-day runs: -19
30-day runs: -40
Model's Last Updated: March 01 2025
image-classification

Introduction of mobileclip_b_lt_timm

Model Details of mobileclip_b_lt_timm

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 MobileCLIP-B (LT) checkpoint for timm.

MobileCLIP Performance Figure

Highlights
  • 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 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

Runs of apple mobileclip_b_lt_timm on huggingface.co

36
Total runs
-2
24-hour runs
-4
3-day runs
-19
7-day runs
-40
30-day runs

More Information About mobileclip_b_lt_timm huggingface.co Model

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mobileclip_b_lt_timm huggingface.co is an AI model on huggingface.co that provides mobileclip_b_lt_timm's model effect (), which can be used instantly with this apple mobileclip_b_lt_timm model. huggingface.co supports a free trial of the mobileclip_b_lt_timm model, and also provides paid use of the mobileclip_b_lt_timm. Support call mobileclip_b_lt_timm model through api, including Node.js, Python, http.

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mobileclip_b_lt_timm install

mobileclip_b_lt_timm is an open source model from GitHub that offers a free installation service, and any user can find mobileclip_b_lt_timm on GitHub to install. At the same time, huggingface.co provides the effect of mobileclip_b_lt_timm install, users can directly use mobileclip_b_lt_timm installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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