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Eva02 Enormous Patch14 Clip 224.laion2b Plus
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Eva02 Enormous Patch14 Clip 224.laion2b Plus

Developed by timm
EVA-CLIP is a large-scale vision-language model based on the CLIP architecture, supporting tasks such as zero-shot image classification.
Text-to-Image
Safetensors
Open Source License:MIT#Zero-shot image classification#Large-scale pretraining#Multimodal understanding
Downloads 54
Release Time : 12/26/2024

Model Overview

This model is a vision-language pretrained model based on the CLIP architecture, capable of understanding the relationship between images and text, suitable for various cross-modal tasks.

Model Features

Zero-shot learning capability
Can perform tasks like image classification without task-specific fine-tuning
Large-scale pretraining
Pretrained on large-scale datasets such as LAION-2B
Cross-modal understanding
Capable of processing and understanding both visual and textual information

Model Capabilities

Zero-shot image classification
Image-text matching
Cross-modal retrieval

Use Cases

Computer vision
Zero-shot image classification
Classify images of new categories without training
Image retrieval
Retrieve relevant images based on text descriptions
Multimodal applications
Image-text matching
Evaluate the matching degree between images and text descriptions
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