v1
latestOpenAPI 3.0.32026-07-2659199427.5 KBGet tokens
Tokenization by MODEL_ID
The tokenization request for the pre-trained and custom embedding use cases and specified embedding modelId (model name) sends text to return results in formats supported by embedding models.
post/ai/tokenization/{MODEL_ID}
Headers
Authorization: Bearer ACCESS_TOKENstring
The authentication and authorization access token.
Content-Typestring
Example:application/json
application/json
Request body
Example request
{
"batch": [
{
"text": "Mr. and Mrs. Dursley and O'\\''Malley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much"
}
],
"useCaseConfig": {
"dataType": "passage"
},
"modelConfig": {
"vectorQuantizationMethod": "min-max",
"dimReductionSize": 256
}
}Response
OK
Example response
{
"generatedTokens": [
{
"tokens": [
"\"[CLS]\", \"query\", \":\", \"mr\", \".\", \"and\", \"mrs\", \".\", \"du\", \"##rs\", \"##ley\", \"and\", \"o\", \"'\", \"malley\", \",\", \"of\", \"number\", \"four\", \",\", \"pri\", \"##vet\", \"drive\", \",\", \"were\", \"proud\", \"to\", \"say\", \"that\", \"they\", \"were\", \"perfectly\", \"normal\", \",\", \"thank\", \"you\", \"very\", \"much\", \".\", \"[SEP]\""
]
}
],
"tokensUsed": {
"promptTokens": 148,
"completionTokens": 27,
"totalTokens": 175
}
}