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Vit Base Patch16 Clip 224.laion400m E32
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Vit Base Patch16 Clip 224.laion400m E32

Developed by timm
Vision Transformer model trained on the LAION-400M dataset, compatible with both open_clip and timm frameworks
Image Classification
Safetensors
Open Source License:MIT#Zero-shot Image Classification#Multimodal CLIP Architecture#LAION-400M Pretraining
Downloads 5,751
Release Time : 10/23/2024

Model Overview

This is a dual-framework compatible Vision Transformer model primarily designed for zero-shot image classification tasks. The model adopts the ViT-B-16 architecture and is trained on the large-scale LAION-400M dataset.

Model Features

Dual Framework Compatibility
Supports both open_clip and timm frameworks, offering more flexible usage options
Large-scale Training Data
Trained on the LAION-400M dataset, covering a wide range of visual concepts
Zero-shot Classification Capability
Capable of performing image classification tasks without task-specific fine-tuning

Model Capabilities

Zero-shot Image Classification
Visual Feature Extraction
Image-Text Alignment

Use Cases

Image Understanding
Zero-shot Image Classification
Classify images of new categories without category-specific training
Image Retrieval
Retrieve relevant images based on text queries
Multimodal Applications
Image Captioning
Generate descriptive text labels for images
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