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POST
/
dedicated
/
v1
/
detokenize
Detokenization
curl --request POST \
  --url https://api.friendli.ai/dedicated/v1/detokenize \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "(endpoint-id)",
  "tokens": [
    128000,
    3923,
    374,
    1803,
    1413,
    15592,
    30
  ]
}
'
{
  "text": "What is generative AI?"
}

Documentation Index

Fetch the complete documentation index at: https://friendli.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

By giving a list of tokens, generate a detokenized output text string. To request successfully, it is mandatory to enter a Personal API Key (e.g. flp_XXX) value in the Bearer Token field. Refer to the authentication section on our introduction page to learn how to acquire this variable and visit here to generate your API Key.

Authorizations

​
Authorization
string
header
required

When using Friendli Suite API for inference requests, you need to provide a Friendli Token for authentication and authorization purposes.

For more detailed information, please refer here.

Headers

​
X-Friendli-Team
string | null

ID of team to run requests as (optional parameter).

Body

application/json
​
model
string
required

ID of target endpoint. If you want to send request to specific adapter, use the format "YOUR_ENDPOINT_ID:YOUR_ADAPTER_ROUTE". Otherwise, you can just use "YOUR_ENDPOINT_ID" alone.

Example:

"(endpoint-id)"

​
tokens
integer[]
required

A token sequence to detokenize.

Example:
[128000, 3923, 374, 1803, 1413, 15592, 30]

Response

Successfully detokenized the tokens.

​
text
string
required

Detokenized text output.

Last modified on April 29, 2026