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Vit Huge Patch14 Clip 224.dfn5b
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Vit Huge Patch14 Clip 224.dfn5b

Developed by timm
A ViT-Huge image encoder based on the CLIP architecture, released by Apple as part of the DFN5B-CLIP model, suitable for visual feature extraction tasks.
Image Classification
Transformers
Open Source License:Other#CLIP visual encoding#large-scale pretraining#zero-shot transfer
Downloads 128
Release Time : 12/26/2024

Model Overview

This model is a Vision Transformer (ViT) implementation of the CLIP architecture, specifically designed for image feature extraction. It employs a huge-scale patch14 structure with an input resolution of 224x224 pixels.

Model Features

Large-scale Vision Transformer
Utilizes ViT-Huge architecture with powerful image feature extraction capabilities
CLIP-compatible design
Developed based on the CLIP framework, can be used in conjunction with text encoders
High-resolution processing
Supports input resolution of 224x224 pixels

Model Capabilities

Image feature extraction
Visual representation learning

Use Cases

Computer vision
Image classification
Extracts image features for classification tasks
Visual search
Generates feature vectors for image retrieval systems
Multimodal applications
Image-text matching
Works with text encoders to achieve cross-modal retrieval
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