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Convnext Base.clip Laion2b Augreg
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Convnext Base.clip Laion2b Augreg

Developed by timm
ConvNeXt Base image encoder based on the CLIP framework, trained on the LAION-2B dataset, supports image feature extraction
Image Classification
Transformers
Open Source License:Apache-2.0#Multimodal Pretraining#Zero-shot Image Classification#Large-scale Visual Representation
Downloads 522
Release Time : 12/24/2024

Model Overview

This model serves as the image encoder component in the CLIP framework, utilizing the ConvNeXt Base architecture and trained on the LAION-2B dataset. It efficiently extracts image features and is suitable for vision-language tasks.

Model Features

Efficient Image Feature Extraction
Utilizes the ConvNeXt Base architecture to efficiently extract meaningful features from images.
Trained on Large-scale Dataset
Trained on the LAION-2B dataset, offering strong generalization capabilities.
CLIP Framework Compatibility
As the image encoder component of the CLIP framework, it can work with text encoders to accomplish cross-modal tasks.

Model Capabilities

Image Feature Extraction
Visual Representation Learning
Cross-modal Alignment

Use Cases

Computer Vision
Image Retrieval
Achieves efficient image retrieval by extracting image features.
Vision-Language Tasks
As part of the CLIP framework, it can be used for tasks such as image-text matching.
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