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clip

Classify images and match text using OpenAI's CLIP model.

Updated Jun 9, 2026
Search Tags:#OpenAI#content moderation#CLIP#image classification#image-text retrieval
One-click install
npx skills add https://github.com/zhouboyu-xreal/Hermes-Memory --skill clip-zhouboyu-xreal
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clip
Source: https://github.com/zhouboyu-xreal/Hermes-Memory/tree/main/optional-skills/mlops/clip
Command: npx skills add https://github.com/zhouboyu-xreal/Hermes-Memory --skill clip-zhouboyu-xreal

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires transformers, torch, pillow, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill empowers users to quickly analyze and classify images using OpenAI's CLIP model, without the need for fine-tuning or extensive data preparation.

Core Features & Use Cases

  • Zero-Shot Image Classification: Automatically classify images into categories without requiring training data.
  • Image-Text Matching: Find images that closely match provided text descriptions.
  • Cross-Modal Retrieval: Retrieve related images for given text queries, or retrieve related text for given images.
  • Content Moderation: Identify inappropriate or harmful content in images.
  • Use Case: You can use this Skill to build a simple image search engine or to create a content moderation tool for your website.

Quick Start

Run 'clip classify --input photo.jpg' to get the top 3 classifications for the image 'photo.jpg'.

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 without training data?▼

Zero-shot image classification automatically categorizes images without training data by using OpenAI's CLIP model. You can classify images by running the command-line interface with your target image file to get the top matching categories.

Can I use CLIP for image-text matching and cross-modal retrieval?▼

Image-text matching with CLIP enables cross-modal retrieval to find closely matching images for text queries or related text for given images. It processes both visual and textual data simultaneously to return relevant results.

Does the CLIP model work for automated content moderation of images?▼

Automated content moderation of images is supported by CLIP to identify inappropriate or harmful visual content. It analyzes image data against textual descriptions to flag unsafe material without requiring fine-tuning.

Do I need PyTorch and the transformers library to run CLIP for image classification?▼

Yes, running CLIP for image classification requires PyTorch, the transformers library, and Pillow for image processing. These dependencies provide the necessary deep learning framework and image handling capabilities.

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