Do inference on multiple models. Note that amount of inferences that will be debited are <amount of texts> * <amount of models called>.
Resource URL
https://api.app.labelf.ai/v2/models/inference
Resource information
Response formats | JSON |
Requires authentication? | Yes - Bearer token |
Path parameters
There are no path parameters.
JSON body parameters
Name | Required | Type | Description | Example |
model_settings | required | List of model_setting objects
(further described in the table below this one) | Specifies which models to use for this inference run. | [ {"model_id":3}, {"model_id":5} ] |
texts | required | List of strings | Specifies the texts that should be inferenced on. | ["Breakfast was not tasty", "breakfast was very good"] |
model_setting object json structure:
Name | Required | Type | Description | Example |
model_id | required | int | defines what model you want to call | 5 |
max_predictions | NOT required | int | Specifies the amount of predictions you want back. For example, setting this to three will yield the three class predictions with the highest probability. You can skip sending this parameter and you will instead get predictions for all classes. | 3 |
label_filter | NOT required | List of strings | If you only want the predictions for certain classes and ignore all other classes, then list those here. Partial matches will also be filtered here, so "po" will filter yield the class "positive". Leaving this out will yield predictions for all classes. | ["positive", "negative"]" |
read_full_text | NOT required | Boolean | Default value is: False
Set this to true if you want the inference model to do a sliding window over the full text instead of truncating it after 512 tokens (~2000-4000 characters). Note that truncation is done during training right now so results can be unexpected. (this will be upgraded as well). | True |
Example Request
POST /v2/models/inference HTTP/1.1 Host: api.app.labelf.ai Authorization: Bearer YOUR_BEARER_TOKEN Content-Type: application/json;charset=UTF-8 { "model_settings": [{"model_id": 33, "max_predictions": 3}, {"model_id": 35}], "texts": ["Breakfast was not tasty"]}Example Curl Request
curl --location --request POST 'https://api.app.labelf.ai/v2/models/inference \ --header 'Authorization: Bearer YOUR_BEARER_TOKEN' \ --header 'Content-Type: application/json' \ --data-raw '{ "model_settings":[{"model_id": 33}, {"model_id": 35}], "texts": ["Breakfast was not tasty"] } 'Example Response
HTTP/1.1 200 OK Status: 200 OK Content-Type: application/json; charset=utf-8 ... "[{"text":"this t-shirt fits me perfectly and looks great","result":[{"predictions":[{"label":"positive","score":0.93},{"label":"neutral","score":0.03}],"model":"sentiment model","model_id":33},{"predictions":[{"label":"does not mention size","score":0.93},{"label":"mentions size","score":0.17}],"model":"mentions size model","model_id":35}]}]"