AIbase
EN
Home
Convnext Base.clip Laiona
C

Convnext Base.clip Laiona

Developed by timm
ConvNeXt Base model based on the CLIP framework, trained on the LAION-Aesthetic dataset, suitable for image feature extraction tasks.
Image Classification
Transformers
Open Source License:Apache-2.0#CLIP visual encoding#Aesthetic feature extraction#Multimodal pre-training
Downloads 14
Release Time : 12/24/2024

Model Overview

This model is the image encoder part of the CLIP (Contrastive Language-Image Pretraining) framework, using the ConvNeXt Base architecture and trained on the LAION-Aesthetic dataset, primarily for extracting high-quality image feature representations.

Model Features

Based on ConvNeXt architecture
Utilizes the modern ConvNeXt architecture, combining the advantages of CNNs and Transformers, providing efficient image feature extraction capabilities.
CLIP framework
As the image encoder part of the CLIP framework, it can learn image representations aligned with text.
Trained on LAION-Aesthetic dataset
Trained on the LAION-Aesthetic dataset, focusing on images with high aesthetic quality.

Model Capabilities

Image feature extraction
Image representation learning

Use Cases

Computer vision
Image retrieval
Use extracted image features for similar image retrieval.
Image classification
Used as a pre-trained model for image classification tasks.
Multimodal learning
Image-text matching
Collaborate with text encoders to achieve image-text matching tasks.
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
English简体中文繁體中文にほんご
© 2025AIbase