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Resnet50 Clip.cc12m
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Resnet50 Clip.cc12m

Developed by timm
CLIP model with ResNet50 architecture trained on the CC12M dataset, supporting zero-shot image classification tasks
Image Classification
Safetensors
Open Source License:MIT#Zero-shot image classification#Dual-framework compatibility#Quick GELU activation
Downloads 233
Release Time : 10/23/2024

Model Overview

This model is a dual-purpose vision-language model compatible with both open_clip and timm frameworks, utilizing ResNet50 architecture with quick GELU activation, suitable for zero-shot image classification tasks

Model Features

Dual-framework compatibility
Supports both open_clip and timm frameworks, offering more flexible usage
Quick GELU activation
Uses quick GELU activation function, potentially improving model training and inference efficiency
Zero-shot learning
Supports zero-shot image classification without task-specific fine-tuning

Model Capabilities

Zero-shot image classification
Image feature extraction
Cross-modal understanding

Use Cases

Computer vision
Image classification
Classify unseen image categories
Visual search
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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