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Convnext Base.clip Laion2b
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Convnext Base.clip Laion2b

Developed by timm
CLIP image encoder based on ConvNeXt architecture, trained by LAION, suitable for multimodal vision-language tasks
Image Classification
Transformers
Open Source License:Apache-2.0#Multimodal Pretraining#Zero-shot Image Classification#Large-scale Visual Representation
Downloads 297
Release Time : 12/24/2024

Model Overview

This model is the image encoder part of the CLIP framework, using ConvNeXt_base architecture, trained on the LAION-2B dataset, capable of encoding images into embeddings aligned with text

Model Features

ConvNeXt Architecture
Utilizes the modern convolutional neural network architecture ConvNeXt, combining the advantages of CNNs and Transformers
Large-scale Pretraining
Trained on the LAION-2B large-scale dataset, possessing robust visual representation capabilities
CLIP Compatibility
Compatible with the CLIP framework and can be used with other CLIP text encoders

Model Capabilities

Image feature extraction
Vision-language alignment
Multimodal embedding generation

Use Cases

Computer Vision
Image Retrieval
Retrieve relevant images through text queries
Zero-shot Classification
Classify new categories without specific training
Multimodal Applications
Image-Text Matching
Assess the matching degree between images and text descriptions
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