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Convnext Xxlarge.clip Laion2b Soup
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Convnext Xxlarge.clip Laion2b Soup

Developed by timm
ConvNeXt-XXLarge image encoder based on the CLIP framework, trained by LAION, suitable for multimodal tasks
Image Classification
Transformers
Open Source License:Apache-2.0#Large-scale visual feature extraction#CLIP architecture optimization#Zero-shot image classification
Downloads 220
Release Time : 12/24/2024

Model Overview

This model is the image encoder part of the CLIP framework, using the ConvNeXt-XXLarge architecture, trained on the LAION-2B dataset, and can be used for image feature extraction and cross-modal representation learning

Model Features

Large-scale pre-training
Trained on the large-scale LAION-2B dataset, with powerful image understanding capabilities
ConvNeXt architecture
Uses the XXLarge version of the modern ConvNeXt architecture, combining the advantages of CNNs and Transformers
CLIP compatibility
As the image encoder part of the CLIP framework, it can work with text encoders to achieve cross-modal learning

Model Capabilities

Image feature extraction
Visual representation learning
Cross-modal alignment

Use Cases

Multimodal applications
Image retrieval
Retrieve relevant images based on text queries
Image classification
Perform zero-shot or few-shot image classification using extracted features
Computer vision
Visual feature extraction
Provide high-quality image representations for downstream tasks
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