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Vit Base Patch16 Plus Clip 240.laion400m E31
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Vit Base Patch16 Plus Clip 240.laion400m E31

Developed by timm
A vision-language dual-purpose model trained on the LAION-400M dataset, supporting zero-shot image classification tasks
Image Classification
Safetensors
Open Source License:MIT#Zero-shot Image Classification#Multimodal Pretraining#Large-scale Visual Understanding
Downloads 37.23k
Release Time : 10/23/2024

Model Overview

This model is a dual-purpose vision model from OpenCLIP and the timm framework, utilizing the ViT-B-16-plus architecture, trained on the LAION-400M dataset, primarily for zero-shot image classification tasks.

Model Features

Dual Framework Compatibility
Supports both OpenCLIP and timm frameworks, offering more flexible usage options
Zero-shot Learning
Performs image classification tasks without fine-tuning
Large-scale Training Data
Trained on the LAION-400M dataset, providing strong generalization capabilities

Model Capabilities

Zero-shot Image Classification
Image Feature Extraction
Vision-Language Alignment

Use Cases

Image Understanding
Zero-shot Image Classification
Classifies images of new categories without specific training
Content Moderation
Identifies inappropriate content in images
Multimodal Applications
Image Retrieval
Retrieves relevant images based on text descriptions
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