{
  "inputs": "The model input",
  "prompt_name": null,
  "normalize": true,
  "truncate": false,
  "truncation_direction": "right"
}

[
  [
    0.038483415,
    -0.00076982786,
    -0.020039458
    ...
  ],
  [
    0.04496114,
    -0.039057795,
    -0.022400795,
    ...
  ]
]

Generating an embedding from a dense embedding model

{
  "inputs": "The model input",
  "prompt_name": null,
  "normalize": true,
  "truncate": false,
  "truncation_direction": "right"
}

[
  [
    0.038483415,
    -0.00076982786,
    -0.020039458
    ...
  ],
  [
    0.04496114,
    -0.039057795,
    -0.022400795,
    ...
  ]
]
​
inputs
string | string[]
required

Inputs that need to be embedded

​
normalize
boolean
default:"true"
​
prompt_name
string

The name of the prompt that should be used by for encoding. If not set, no prompt will be applied.

Must be a key in the sentence-transformers configuration prompts dictionary.

For example if prompt_name is “doc” then the sentence “How to get fast inference?” will be encoded as “doc: How to get fast inference?” because the prompt text will be prepended before any text to encode.

​
truncate
boolean
default:"false"

Automatically truncate inputs that are longer than the maximum supported size

​
truncate_direction
"right" | "left"
default:"right"