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Vit Large Patch14 Clip 224.dfn2b
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Vit Large Patch14 Clip 224.dfn2b

Developed by timm
A vision transformer model based on the CLIP architecture, focused on image feature extraction, released by Apple.
Image Classification
Transformers
Open Source License:Other#CLIP visual encoding#Zero-shot classification#Multimodal feature extraction
Downloads 178
Release Time : 12/26/2024

Model Overview

This model is the image encoder part of CLIP (Contrastive Language-Image Pretraining), utilizing the Vision Transformer (ViT) architecture, suitable for image feature extraction tasks.

Model Features

Based on CLIP architecture
Uses a contrastive learning framework capable of learning joint representations of images and text.
Vision Transformer
Processes images using the ViT architecture, dividing images into patch sequences for processing.
Large-scale pretraining
Pretrained on large datasets, possessing robust feature extraction capabilities.

Model Capabilities

Image feature extraction
Image representation learning

Use Cases

Computer vision
Image retrieval
Uses extracted image features for similar image retrieval.
Visual question answering
Serves as the image encoder for visual question answering systems.
Multimodal learning
Image-text matching
Used for cross-modal matching tasks between images and text.
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