Eva Giant Patch14 Clip 224.laion400m S11b B41k
A vision-language model based on the CLIP architecture, supporting zero-shot image classification tasks
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Release Time : 4/10/2023
Model Overview
This model is a vision-language model based on the CLIP architecture, capable of mapping images and text into the same semantic space for cross-modal similarity computation and zero-shot image classification.
Model Features
Zero-shot Learning Capability
Can perform new visual tasks without task-specific fine-tuning
Cross-modal Understanding
Capable of understanding both image and text content, establishing semantic connections between them
Large-scale Pre-training
Pre-trained on large-scale datasets such as LAION-400M
Model Capabilities
Zero-shot Image Classification
Image-Text Matching
Cross-modal Retrieval
Use Cases
Content Moderation
Inappropriate Content Detection
Automatically identify potentially inappropriate content in images
E-commerce
Product Categorization
Classify product images based on natural language descriptions
Media Analysis
Image Captioning
Generate semantically relevant text descriptions for images
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