clip
SkillSearchOpenAI CLIP — contrastive language-image pre-training. Zero-shot image classification, image-text similarity, concept search, and cross-modal retrieval. Embed images and text into shared space.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the clip skill
What this skill tells your AI
The instructions your AI receives, as published by mkurman/zorai in skills/scientific-skills/clip/SKILL.md and read by ahel’s review.
Overview
OpenAI CLIP (Contrastive Language-Image Pre-training) learns joint text-image representations. Enables zero-shot image classification, image-text similarity, cross-modal search, and image captioning without task-specific training.
Installation
uv pip install openai-clip
Zero-Shot Classification
import clip
import torch
model, preprocess = clip.load("ViT-B/32")
image = preprocess(load_image("photo.jpg")).unsqueeze(0)
text = clip.tokenize(["a dog", "a cat", "a bird"])
with torch.no_grad():
logits, _ = model(image, text)
probs = logits.softmax(dim=-1)
print(f"Predicted: class {probs.argmax().item()} with {probs.max():.2%} confidence")
Text-Image Similarity
images = torch.stack([preprocess(img) for img in [load_image("a.jpg"), load_image("b.jpg")]])
texts = clip.tokenize(["sunset", "ocean", "mountain"])
with torch.no_grad():
similarity = model(images, texts)[0].softmax(dim=-1)
References
Signals
- GitHub stars
- 324
- Forks
- 26
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
clip-mkurman- Source
- github.com/mkurman/zorai