• sentence-transformers/all-mpnet-base-v2 Model Card on the Hugging Face Hub
• Text Embeddings Inference Documentation

Send Request

curl <AZUREML_ENDPOINT_URL> \
    -X POST \
    -d '{"model":"sentence-transformers/all-mpnet-base-v2","input":"What is Deep Learning?"}' \
    -H "Authorization: Bearer <AZUREML_TOKEN>" \
    -H "Content-Type: application/json"

Supported Parameters

• model (string): ID of the model to use, in this case it should default to sentence-transformers/all-mpnet-base-v2.
• input (string or array): Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for all embedding models), cannot be an empty string, and any array must be 2048 dimensions or less.
• dimensions (integer, optional): The number of dimensions the resulting output embeddings should have.
• encoding_format (string, optional): The format to return the embeddings in. Can be either "float" or "base64". Defaults to "float".
• user (string, optional): A unique identifier representing your end-user.

Example payload

{
  "model": "sentence-transformers/all-mpnet-base-v2",
  "input": "What is Deep Learning?",
  "encoding_format": "float"
}