clip-vit-large-patch14

by openai

Contrastive Language-Image Pre-Training for zero-shot visual understanding

6.9Mdl/month

1,966likes

428Mparams

HuggingFace Use in Pipeline

Identifiers

Model ID

openai/clip-vit-large-patch14

Feature URI

mixpeek://video_descriptor@v1/openai_clip_large_v1

Overview

CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on 400M image-text pairs from the internet. It learns visual concepts from natural language supervision, enabling zero-shot transfer to downstream tasks without task-specific training data.

On Mixpeek, CLIP powers visual embedding extraction — converting video frames and images into 768-dimensional vectors that capture semantic meaning. This enables similarity search across visual content using natural language queries.

Architecture

Vision Transformer (ViT-L/14) with 24 layers, 1024-dim hidden size, 16 attention heads. Text encoder is a 12-layer transformer. Both encoders project into a shared 768-dim embedding space via contrastive learning.

Mixpeek SDK Integration

import { Mixpeek } from "mixpeek";

const mx = new Mixpeek({ apiKey: "API_KEY" });

// Upload and extract visual embeddings
await mx.collections.ingest({
  collection_id: "my-collection",
  source: { url: "https://example.com/video.mp4" },
  feature_extractors: [{
    name: "image_embedding",
    version: "v1",
    params: {
      model_id: "openai/clip-vit-large-patch14"
    }
  }]
});