hf_classify: Text Classification

In huggingfaceR: Access 'Hugging Face' Models and Datasets

Text Classification

Description

Classify text using a Hugging Face model. Commonly used for sentiment analysis, topic classification, etc. Vector inputs are sent in a single batched Inference API request when possible, which is substantially faster than one API request per text.

Usage

hf_classify(
  text,
  model = hf_default_model("classify"),
  token = NULL,
  endpoint_url = NULL,
  ...
)

Arguments

text	Character vector of text(s) to classify.
model	Character string. Model ID from Hugging Face Hub. Default: "distilbert/distilbert-base-uncased-finetuned-sst-2-english" (sentiment analysis).
token	Character string or NULL. API token for authentication.
endpoint_url	Character string or NULL. A custom Inference Endpoint URL. When provided, requests are sent to this URL instead of the public Inference API. Use for models deployed on dedicated Inference Endpoints.
...	Additional arguments (currently unused).

Value

A tibble with columns: text, label, score

Examples

## Not run: 
# Sentiment analysis
hf_classify("I love R programming!")

# Multiple texts
hf_classify(c("This is great!", "This is terrible."))

# Use in a pipeline
library(dplyr)
reviews |>
  mutate(sentiment = hf_classify(review_text)) |>
  unnest(sentiment)

## End(Not run)

huggingfaceR documentation built on Aug. 30, 2026, 1:06 a.m.