---
title: bge-large-en-v1.5
description: BAAI general embedding (Large) model that transforms any given text into a 1024-dimensional vector
image: https://developers.cloudflare.com/dev-products-preview.png
---

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#  bge-large-en-v1.5 

Text Embeddings • BAAI 

`@cf/baai/bge-large-en-v1.5` 

BAAI general embedding (Large) model that transforms any given text into a 1024-dimensional vector

| Model Info           |                                                         |
| -------------------- | ------------------------------------------------------- |
| More information     | [link ↗](https://huggingface.co/BAAI/bge-large-en-v1.5) |
| Maximum Input Tokens | 512                                                     |
| Output Dimensions    | 1,024                                                   |
| Batch                | Yes                                                     |
| Unit Pricing         | $0.20 per M input tokens                                |

## Usage

* [  TypeScript ](#tab-panel-4944)
* [  Python ](#tab-panel-4945)
* [  curl ](#tab-panel-4946)

```
export interface Env {  AI: Ai;}
export default {  async fetch(request, env): Promise<Response> {
    // Can be a string or array of strings]    const stories = [      "This is a story about an orange cloud",      "This is a story about a llama",      "This is a story about a hugging emoji",    ];
    const embeddings = await env.AI.run(      "@cf/baai/bge-large-en-v1.5",      {        text: stories,      }    );
    return Response.json(embeddings);  },} satisfies ExportedHandler<Env>;
```

```
import osimport requests

ACCOUNT_ID = "your-account-id"AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")
stories = [  'This is a story about an orange cloud',  'This is a story about a llama',  'This is a story about a hugging emoji']
response = requests.post(  f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/baai/bge-large-en-v1.5",  headers={"Authorization": f"Bearer {AUTH_TOKEN}"},  json={"text": stories})
print(response.json())
```

Terminal window

```
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/baai/bge-large-en-v1.5  \  -X POST  \  -H "Authorization: Bearer $CLOUDFLARE_API_TOKEN"  \  -d '{ "text": ["This is a story about an orange cloud", "This is a story about a llama", "This is a story about a hugging emoji"] }'
```

OpenAI compatible endpoints 

Workers AI also supports OpenAI compatible API endpoints for `/v1/chat/completions` and `/v1/embeddings`. For more details, refer to [Configurations ](https://developers.cloudflare.com/workers-ai/configuration/open-ai-compatibility/). 

## Parameters

Synchronous — Send a request and receive a complete response 

* [ Input ](#tab-panel-4947)
* [ Output ](#tab-panel-4948)

▶text

`one of`required

pooling

`string`default: meanenum: mean, clsThe pooling method used in the embedding process. \`cls\` pooling will generate more accurate embeddings on larger inputs - however, embeddings created with cls pooling are not compatible with embeddings generated with mean pooling. The default pooling method is \`mean\` in order for this to not be a breaking change, but we highly suggest using the new \`cls\` pooling for better accuracy.

▶shape\[\]

`array`

▶data\[\]

`array`Embeddings of the requested text values

pooling

`string`enum: mean, clsThe pooling method used in the embedding process.

Batch — Send multiple requests in a single API call 

* [ Input ](#tab-panel-4949)
* [ Output ](#tab-panel-4950)

▶requests\[\]

`array`requiredBatch of the embeddings requests to run using async-queue

▶shape\[\]

`array`

▶data\[\]

`array`Embeddings of the requested text values

pooling

`string`enum: mean, clsThe pooling method used in the embedding process.

## API Schemas (Raw)

 Synchronous Input [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/sync-input.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/sync-input.json "Download") 

 Synchronous Output [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/sync-output.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/sync-output.json "Download") 

 Batch Input [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/batch-input.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/batch-input.json "Download") 

 Batch Output [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/batch-output.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/bge-large-en-v1.5/batch-output.json "Download")

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```