Inference Providers documentation

Token Classification

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Token Classification

Token classification is a task in which a label is assigned to some tokens in a text. Some popular token classification subtasks are Named Entity Recognition (NER) and Part-of-Speech (PoS) tagging.

For more details about the token-classification task, check out its dedicated page! You will find examples and related materials.

Recommended models

Explore all available models and find the one that suits you best here.

Using the API

from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="hf-inference",
    api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxx",
)

result = client.token_classification(
    inputs="My name is Sarah Jessica Parker but you can call me Jessica",
    model="dslim/bert-base-NER",
)

API specification

Request

Headers
authorization string Authentication header in the form 'Bearer: hf_****' when hf_**** is a personal user access token with “Inference Providers” permission. You can generate one from your settings page.
Payload
inputs* string The input text data
parameters object
        ignore_labels string[] A list of labels to ignore
        stride integer The number of overlapping tokens between chunks when splitting the input text.
        aggregation_strategy string One of the following:
                 (#1) ’none’ Do not aggregate tokens
                 (#2) ’simple’ Group consecutive tokens with the same label in a single entity.
                 (#3) ’first’ Similar to “simple”, also preserves word integrity (use the label predicted for the first token in a word).
                 (#4) ’average’ Similar to “simple”, also preserves word integrity (uses the label with the highest score, averaged across the word’s tokens).
                 (#5) ’max’ Similar to “simple”, also preserves word integrity (uses the label with the highest score across the word’s tokens).

Response

Body
(array) object[] Output is an array of objects.
        entity_group string The predicted label for a group of one or more tokens
        entity string The predicted label for a single token
        score number The associated score / probability
        word string The corresponding text
        start integer The character position in the input where this group begins.
        end integer The character position in the input where this group ends.
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