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`@tensorflow/tfjs-backend-webgl`:\n\n```sh\nnpm i @tensorflow/tfjs-backend-webgl\n```\n\nIf you're using Orama in Node.js, we recommend using `@tensorflow/tfjs-node`:\n\n```sh\nnpm i @tensorflow/tfjs-node\n```\n\n## Usage\n\n```js\nimport { create } from '@orama/orama'\nimport { pluginEmbeddings } from '@orama/plugin-embeddings'\nimport '@tensorflow/tfjs-node' // Or any other appropriate TensorflowJS backend\n\nconst plugin = await pluginEmbeddings({\n  embeddings: {\n    defaultProperty: 'embeddings', // Property used to store generated embeddings\n    onInsert: {\n      generate: true, // Generate embeddings at insert-time\n      properties: ['description'], // properties to use for generating embeddings at insert time\n      verbose: true,\n    }\n  }\n})\n\nconst db = await create({\n  schema: {\n    description: 'string',\n    embeddings: 'vector[512]' // Orama generates 512-dimensions vectors\n  },\n  plugins: [plugin]\n})\n```\n\nExample usage at insert time:\n\n```js\nawait 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