---
title: DeepInfra | Developer Documentation
---

To use DeepInfra embeddings, you need to import `DeepInfraEmbedding` from llamaindex. Check out available embedding models [here](https://deepinfra.com/models/embeddings).

## Installation

```
npm i llamaindex @llamaindex/deepinfra
```

```
import { Document, Settings, VectorStoreIndex } from "llamaindex";
import { DeepInfraEmbedding } from "@llamaindex/deepinfra";


// Update Embed Model
Settings.embedModel = new DeepInfraEmbedding();


const document = new Document({ text: essay, id_: "essay" });


const index = await VectorStoreIndex.fromDocuments([document]);


const queryEngine = index.asQueryEngine();


const query = "What is the meaning of life?";


const results = await queryEngine.query({
  query,
});
```

By default, DeepInfraEmbedding is using the sentence-transformers/clip-ViT-B-32 model. You can change the model by passing the model parameter to the constructor. For example:

```
import { DeepInfraEmbedding } from "@llamaindex/deepinfra";


const model = "intfloat/e5-large-v2";
Settings.embedModel = new DeepInfraEmbedding({
  model,
});
```

You can also set the `maxRetries` and `timeout` parameters when initializing `DeepInfraEmbedding` for better control over the request behavior.

For example:

```
import { Settings } from "llamaindex";
import { DeepInfraEmbedding } from "@llamaindex/deepinfra";


const model = "intfloat/e5-large-v2";
const maxRetries = 5;
const timeout = 5000; // 5 seconds


Settings.embedModel = new DeepInfraEmbedding({
  model,
  maxRetries,
  timeout,
});
```

Standalone usage:

```
import { DeepInfraEmbedding } from "@llamaindex/deepinfra";
import { config } from "dotenv";
// For standalone usage, you need to configure DEEPINFRA_API_TOKEN in .env file
config();


const main = async () => {
  const model = "intfloat/e5-large-v2";
  const embeddings = new DeepInfraEmbedding({ model });
  const text = "What is the meaning of life?";
  const response = await embeddings.embed([text]);
  console.log(response);
};


main();
```

For questions or feedback, please contact us at <feedback@deepinfra.com>

## API Reference

- [DeepInfraEmbedding](/typescript/framework-api-reference/classes/deepinfraembedding/index.md)