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    Text Embedding

    Extract semantic embeddings from documents, transcripts and text content

    Note: This playground provides simulated output to showcase functionality. No input data is processed or stored on our servers. Use this demo to explore the feature extractor's capabilities before integrating it into your application.

    Input

    Enter the text you want to process

    The embedding model to use. Default: text-embedding-3-large

    Whether to truncate long texts. Default: true

    Whether to normalize the embeddings. Default: true

    Output

    {
      "embedding": [
        0.024,
        -0.015,
        0.128,
        0.035,
        "..."
      ],
      "dimensions": 1536,
      "model": "text-embedding-3-large",
      "text_chunk": "Sample text content for embedding generation",
      "token_count": 128,
      "truncated": false,
      "normalized": true
    }

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    Text Embedding: common questions

    How much does the Text Embeddings (E5-Large) extractor cost?
    1 cr/1k_tokens. Credits are billed per unit processed; see mixpeek.com/pricing for the credit rate.
    What file types does Text Embeddings (E5-Large) support?
    Text. It produces embeddings from multilingual_e5_large_instruct_v1.

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