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Eva02 Base Patch16 Clip 224.merged2b
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Eva02 Base Patch16 Clip 224.merged2b

Developed by timm
The EVA CLIP model is a vision-language model built on the OpenCLIP and timm frameworks, supporting tasks like zero-shot image classification.
Text-to-Image
Safetensors
Open Source License:MIT#Zero-shot image classification#Multimodal understanding#High-precision visual representation
Downloads 3,029
Release Time : 12/26/2024

Model Overview

This model combines the EVA architecture and CLIP framework, enabling the understanding of relationships between images and text, suitable for multimodal tasks.

Model Features

Zero-shot learning
Performs image classification tasks without task-specific fine-tuning.
Multimodal understanding
Capable of processing and understanding both image and text information simultaneously.
Efficient architecture
Combines EVA02 and CLIP frameworks to balance 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
Performs well on multiple benchmark datasets
Image retrieval
Retrieve relevant images based on text descriptions
Content moderation
Inappropriate content detection
Identify potentially inappropriate content in images
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