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Eva02 Large Patch14 Clip 224.merged2b
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Eva02 Large Patch14 Clip 224.merged2b

Developed by timm
The EVA CLIP model is a vision-language model based on OpenCLIP and timm model weights, supporting tasks such as zero-shot image classification.
Image Classification
Safetensors
Open Source License:MIT#Zero-shot image classification#Multimodal contrastive learning#High-resolution image processing
Downloads 165
Release Time : 12/26/2024

Model Overview

This model combines the advantages of EVA and CLIP architectures for handling multimodal tasks involving vision and language, with particular expertise in zero-shot image classification.

Model Features

Zero-shot learning capability
Can perform image classification tasks without task-specific fine-tuning
Multimodal understanding
Capable of processing both visual and linguistic information
Efficient architecture
Based on an improved CLIP architecture, balancing performance and efficiency

Model Capabilities

Zero-shot image classification
Image-text matching
Multimodal feature extraction

Use Cases

Computer vision
Image classification
Classify unseen image categories
Achieves good performance in zero-shot settings
Content moderation
Identify inappropriate content in images
Multimodal applications
Image search
Search for relevant images based on text descriptions
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