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Vit Large Patch14 Clip 224.datacompxl
A vision Transformer model based on the CLIP architecture, specifically designed for image feature extraction, released by the LAION organization.
Downloads 14
Release Time : 12/24/2024
Model Overview
This model is the image encoder part of CLIP (Contrastive Language-Image Pretraining), employing the ViT-Large architecture. It is trained on large-scale image-text pairs and can extract high-quality image feature representations.
Model Features
Large-scale Pretraining
Pretrained using the DataComp XL dataset (s13B-b90K), which contains large-scale image-text pair data.
High-resolution Processing
Supports input resolution of 224x224 pixels, capable of capturing finer image features.
Contrastive Learning Framework
Trained based on CLIP's contrastive learning framework, learning a joint representation space for images and text.
Model Capabilities
Image Feature Extraction
Image-Text Alignment
Zero-shot Image Classification
Image Retrieval
Use Cases
Computer Vision
Zero-shot Image Classification
Classify images without specific training.
Performs excellently on multiple benchmark tests.
Image Retrieval
Retrieve relevant images based on text queries.
Capable of achieving high-quality cross-modal retrieval.
Multimodal Applications
Image Captioning
Automatically generate descriptive text for images.
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