sentence-transformers/all-mpnet-base-v2 cover image

sentence-transformers/all-mpnet-base-v2

A sentence transformation model that has been trained on a wide range of datasets, including but not limited to S2ORC, WikiAnwers, PAQ, Stack Exchange, and Yahoo! Answers. Our model can be used for various NLP tasks such as clustering, sentiment analysis, and question answering.

A sentence transformation model that has been trained on a wide range of datasets, including but not limited to S2ORC, WikiAnwers, PAQ, Stack Exchange, and Yahoo! Answers. Our model can be used for various NLP tasks such as clustering, sentiment analysis, and question answering.

Public
$0.005 / Mtoken
512

HTTP/cURL API

You can use cURL or any other http client to run inferences:

curl -X POST \
    -H "Authorization: bearer $DEEPINFRA_TOKEN"  \
    -F 'inputs=["I like chocolate"]'  \
    'https://api.deepinfra.com/v1/inference/sentence-transformers/all-mpnet-base-v2'

which will give you back something similar to:

{
  "embeddings": [
    [
      0.0,
      0.5,
      1.0
    ],
    [
      1.0,
      0.5,
      0.0
    ]
  ],
  "input_tokens": 42,
  "request_id": null,
  "inference_status": {
    "status": "unknown",
    "runtime_ms": 0,
    "cost": 0.0,
    "tokens_generated": 0,
    "tokens_input": 0
  }
}

Input fields

inputsarray

sequences to embed

Default value: []


normalizeboolean

whether to normalize the computed embeddings

Default value: false


imagestring

image to embed


webhookfile

The webhook to call when inference is done, by default you will get the output in the response of your inference request

Input Schema

Output Schema