clip

Classify images and search by text using OpenAI's CLIP model.

6|3|Updated Jan 29, 2026

Search Tags:#semantic search #content classification #vision-language #image classification #image moderation

Ready to run

npx skills add https://github.com/jonnabio/ace-framework --skill clip-jonnabio

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: clip
Source: https://github.com/jonnabio/ace-framework/tree/main/.ace/packs/ai-research/clip
Command: npx skills add https://github.com/jonnabio/ace-framework --skill clip-jonnabio

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill enables users to classify images and perform semantic image search without fine-tuning, simplifying tasks like image recognition and content moderation.

Core Features & Use Cases

Zero-Shot Image Classification: Identify the type of image (e.g., "a dog") without the need for training data.
Image-Text Similarity: Match images to text descriptions and search for images that best match a text query.
Content Moderation: Classify images for safe for work, not safe for work, and other categories.
Use Case: Automatically moderate content for NSFW material by using CLIP to classify images as appropriate categories.

Quick Start

Run the CLIP skill to classify an image file 'sample.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 providing training data?▼

Semantic image search matches text queries to image embeddings using the CLIP vision-language model. This Skill enables you to find images that best match a text description by calculating image-text similarity scores without needing a trained search index.

Can I use CLIP for automated content moderation to detect NSFW images?▼

Yes, you can use CLIP for content moderation to classify images as safe for work or not safe for work. This Skill applies the vision-language model to assess content safety and categorize images automatically without fine-tuning.

Do I need PyTorch and TorchVision to run image-text similarity tasks?▼

Yes, PyTorch and TorchVision are required dependencies to run image-text similarity tasks with this Skill. You also need the Pillow library to process and load the image files before the CLIP model can analyze them.

What are the limitations of using a zero-shot model for image classification?▼

Zero-shot image classification using CLIP relies on pre-trained vision-language alignments rather than fine-tuned domain knowledge. This means it may struggle with highly specialized categories or nuanced content moderation edge cases that require custom training data to recognize accurately.