hf_extract_topics: Extract Semantic Topics from Text

In huggingfaceR: Access 'Hugging Face' Models and Datasets

Extract Semantic Topics from Text

Description

Identify semantic topics by clustering embeddings and extracting representative keywords from each cluster.

Usage

hf_extract_topics(data, text_col = "text", k = 5, top_n = 10)

Arguments

data	A data frame with text and embeddings.
text_col	Character string. Name of text column.
k	Integer. Number of topics/clusters. Default: 5.
top_n	Integer. Number of top words per topic. Default: 10.

Value

A tibble with topics and their top terms.

Examples

## Not run: 
library(tidytext)

# Extract topics
topics <- docs_embedded |>
  hf_extract_topics(text_col = "text", k = 3, top_n = 5)

## End(Not run)

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