hf_ez_sentence_similarity: Compare Sentence Similarity Semantically

In huggingfaceR: Access 'Hugging Face' Models and Datasets

Compare Sentence Similarity Semantically

Description

Calculate the semantic similarity between one text and a list of other sentences by comparing their embeddings.

Usage

hf_ez_sentence_similarity(
  model_id = "sentence-transformers/all-MiniLM-L6-v2",
  use_api = FALSE
)

Arguments

model_id	A model_id. Run hf_search_models(...) for model_ids. Defaults to 'sentence-transformers/all-MiniLM-L6-v2'.
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 sentence similarity object

See Also

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

Examples

## Not run: 
# Load the default model and use local inference
ez <- hf_ez_sentence_similarity()
ez$infer(
  source_sentence = "That is a happy person",
  sentences = list(
    "That is a happy dog",
    "That is a very happy person",
    "Today is a sunny day"
  )
)

# Use the API for inference.
ez <- hf_ez_sentence_similarity(use_api = TRUE)
ez$infer(
  source_sentence = "That is a happy person",
  sentences = list(
    "That is a happy dog",
    "That is a very happy person",
    "Today is a sunny day"
  )
)

## End(Not run)

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