This file is byte-identical to the first copy the registry indexed, one of 5 indexed copies. Same content hash, so the same checks give both the same grade.
clip from jensen-yao/agents-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# CLIP - Contrastive Language-Image Pre-Training
OpenAI's model that understands images from natural language.
## When to use CLIP
**Use when:**
- Zero-shot image classification (no training data needed)
- Image-text similarity/matching
- Semantic image search
- Content moderation (detect NSFW, violence)
- Visual question answering
- Cross-modal retrieval (image→text, text→image)
**Metrics**:
- **25,300+ GitHub stars**
- Trained on 400M image-text pairs
- Matches ResNet-50 on ImageNet (zero-shot)
- MIT License
**Use alternatives instead**:
- **BLIP-2**: Better captioning
- **LLaVA**: Vision-language chat
- **Segment Anything**: Image segmentation
## Quick start
### Installation
```bash
pip install git+https://github.com/openai/CLIP.git
pip install torch torchvision ftfy regex tqdm
```
### Zero-shot classification
```python
import torch
import clip
from PIL import Image
# Load model
device = "cuda" if torch.cuda.is_available() else "cpu"
model, preprocess = clip.load("ViT-B/32", device=device)
# Load image
image = preprocess(Image.open("photo.jpg")).unsqueeze(0).to(device)
# Define possible labels
text = clip.tokenize(["a dog", "a cat", "a bird", "a car"]).to(device)
…
The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
GET https://markdownregistry.com/api/v1/artifacts/art_g7hewhwke53o3d6f
GET https://markdownregistry.com/api/v1/resolve?ref=jensen-yao/agents-skills/clip
GET https://markdownregistry.com/api/v1/blob/9fcacf1c041d71ef1e61c7cac2bb7a2c42c3d19d6c2a0fc2e5f5a3c9641b7a3e
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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mikeprasad/aria-knowledge · plugin-antigravity/skills/.archived/clip/SKILL.md · Save a URL or text snippet to the knowledge intake for later review. Use when user says '/clip', '/save', 'clip this'…
mikeprasad/aria-knowledge · plugin-openai-codex/skills/.archived/clip/SKILL.md · Save a URL, snippet, or pasted note into ARIA clippings for later audit. Trigger on /clip, /save, clip this, save this…
mikeprasad/aria-knowledge · plugin-claude-code/skills/.archived/clip/SKILL.md · Save a URL or text snippet to the knowledge intake for later review. Use when user says '/clip', '/save', 'clip this'…
mikeprasad/aria-knowledge · plugin-claude-cowork/skills/.archived/clip/SKILL.md · Save a URL or text snippet to the knowledge intake for later review. Use when user says "/aria-cowork:clip" or…
