clip

Name: clip
Availability: InStock
Author: gregsgreycode

Connect images and text for zero-shot classification and cross-modal retrieval.

6|2|Updated Mar 19, 2026

Search Tags:#multimodal #zero-shot #clip #vision-language #image-search #cross-modal

Ready to run

npx skills add https://github.com/GregsGreyCode/Logos --skill clip-gregsgreycode

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: clip
Source: https://github.com/GregsGreyCode/Logos/tree/main/skills/mlops/models/clip
Command: npx skills add https://github.com/GregsGreyCode/Logos --skill clip-gregsgreycode

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

CLIP enables connecting images and text to perform zero-shot classification, image-text similarity, and cross-modal retrieval without task-specific training.

Core Features & Use Cases

Zero-shot image classification with natural language prompts.
Image-text similarity and cross-modal retrieval across datasets.
Content moderation, visual search, and multimodal QA applications.

Quick Start

Install and load a CLIP model, then run a simple zero-shot classification on your image with a set of text prompts.

Frequently Asked Questions about clip

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform zero-shot image classification using natural language prompts?▼

Zero-shot image classification uses pre-trained vision-language models to connect images and text, allowing you to categorize images against natural language prompts without task-specific training.

What is cross-modal retrieval and how does it work for image search?▼

Cross-modal retrieval bridges vision and language by generating image-text embeddings, enabling you to match and retrieve relevant images from datasets using text queries.

Can I use CLIP for visual question answering and content moderation?▼

Yes, CLIP supports multimodal QA and content moderation workflows by calculating image-text similarity to evaluate visual content against descriptive text criteria.

Do I need task-specific training data for cross-modal retrieval across datasets?▼

No, cross-modal retrieval across datasets does not require task-specific training data because the Skill utilizes pre-trained weights to connect images and text directly.

What are the limitations of using zero-shot prompts for image-text similarity?▼

Zero-shot prompts rely entirely on pre-trained weights, meaning image-text similarity accuracy is constrained by the model's existing vision-language knowledge and may require careful prompt engineering.