hf_ez_summarization: Summarize a Text

In huggingfaceR: Access 'Hugging Face' Models and Datasets

Summarize a Text

Description

This task is well known to summarize longer text into shorter text. Be careful, some models have a maximum length of input. That means that the summary cannot handle full books for instance. Be careful when choosing your model.

Usage

hf_ez_summarization(model_id = "facebook/bart-large-cnn", use_api = FALSE)

Arguments

model_id	A model_id. Run hf_search_models(...) for model_ids. Defaults to 'facebook/bart-large-cnn'.
use_api	Whether to use the Inference API to run the model (TRUE) or download and run the model locally (FALSE). Defaults to FALSE

Value

A summarization object

See Also

https://huggingface.co/docs/api-inference/detailed_parameters#summarization-task

Examples

## Not run: 
# Load the default model and use local inference
ez <- hf_ez_summarization()
text <- paste(
  "The Eiffel Tower is 324 metres tall and located in Paris.",
  "It was the world's tallest man-made structure for 41 years."
)
ez$infer(string = text, min_length = 10, max_length = 40)

# Load a specific model and use the API for inference.
ez <- hf_ez_summarization(model_id = 'xlm-roberta-base', use_api = TRUE)
ez$infer(string = "huggingface is the <mask>!")

## End(Not run)

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