hf_question_answer: Extractive Question Answering

In huggingfaceR: Access 'Hugging Face' Models and Datasets

Extractive Question Answering

Description

Answer a question from a supplied context passage using an extractive question-answering model via the Hugging Face Inference Providers API. The answer is a span extracted verbatim from the context. 'question' and 'context' are recycled to a common length (each may be length 1).

Usage

hf_question_answer(
  question,
  context,
  model = hf_default_model("question_answer"),
  token = NULL,
  endpoint_url = NULL,
  ...
)

Arguments

question	Character vector of question(s).
context	Character vector of context passage(s) to answer from.
model	Character string. Model ID from the Hugging Face Hub. Append '":provider"' to select an inference provider. Default: "deepset/roberta-base-squad2".
token	Character string or NULL. API token for authentication.
endpoint_url	Character string or NULL. A custom Inference Endpoint URL.
...	Additional arguments (currently unused).

Value

A tibble with columns: question, answer, score, start, end.

See Also

https://huggingface.co/docs/inference-providers/tasks/question-answering

Examples

## Not run: 
hf_question_answer(
  question = "Where was Obama born?",
  context = "Barack Obama was born in Honolulu, Hawaii."
)

# One context, several questions
hf_question_answer(
  question = c("Who?", "Where?"),
  context = "Ada Lovelace worked in London."
)

## End(Not run)

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