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bge-base-en-v1.5

Text Embeddings • BAAI • Hosted

BAAI general embedding (Base) model that transforms any given text into a 768-dimensional vector

Model Info
Context Window ↗153,600 tokens
More informationlink ↗
Maximum Input Tokens512
Output Dimensions768
BatchYes
Unit Pricing$0.067 per M input tokens

Usage

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-base-en-v1.5",
      {
        text: stories,
      }
    );


    return Response.json(embeddings);
  },
} satisfies ExportedHandler<Env>;

Parameters

Synchronous — Send a request and receive a complete response
pooling
stringdefault: 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.
Batch — Send multiple requests in a single API call

API Schemas (Raw)

Synchronous — Send a request and receive a complete response 
{
  "properties": {
    "text": {
      "oneOf": [
        {
          "type": "string",
          "description": "The text to embed",
          "minLength": 1
        },
        {
          "type": "array",
          "description": "Batch of text values to embed",
          "items": {
            "type": "string",
            "description": "The text to embed",
            "minLength": 1
          },
          "maxItems": 100
        }
      ]
    },
    "pooling": {
      "type": "string",
      "enum": [
        "mean",
        "cls"
      ],
      "default": "mean",
      "description": "The 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."
    }
  },
  "required": [
    "text"
  ]
}
Batch — Send multiple requests in a single API call 
{
  "properties": {
    "requests": {
      "type": "array",
      "description": "Batch of the embeddings requests to run using async-queue",
      "items": {
        "properties": {
          "text": {
            "oneOf": [
              {
                "type": "string",
                "description": "The text to embed",
                "minLength": 1
              },
              {
                "type": "array",
                "description": "Batch of text values to embed",
                "items": {
                  "type": "string",
                  "description": "The text to embed",
                  "minLength": 1
                },
                "maxItems": 100
              }
            ]
          },
          "pooling": {
            "type": "string",
            "enum": [
              "mean",
              "cls"
            ],
            "default": "mean",
            "description": "The 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."
          }
        },
        "required": [
          "text"
        ]
      }
    }
  },
  "required": [
    "requests"
  ]
}