R/transforEmotion.R

In transforEmotion: Sentiment Analysis for Text, Image and Video using Transformer Models

#' transforEmotion--package
#' 
#' @description Implements sentiment and emotion analysis using \href{https://huggingface.co}{huggingface} transformer
#' zero-shot classification model pipelines on text and image data. The default text pipeline is
#' \href{https://huggingface.co/cross-encoder/nli-distilroberta-base}{Cross-Encoder's DistilRoBERTa} and default image/video pipeline
#' is \href{https://huggingface.co/openai/clip-vit-base-patch32}{Open AI's CLIP}. All other zero-shot classification model pipelines can be implemented using
#' their model name from \href{https://huggingface.co/models?pipeline_tag=zero-shot-classification}{https://huggingface.co/models?pipeline_tag=zero-shot-classification}.
#' 
#' @references
#' Yin, W., Hay, J., & Roth, D. (2019).
#' Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach.
#' arXiv preprint arXiv:1909.00161.
#' 
#' @author Alexander P. Christensen <alexpaulchristensen@gmail.com>, Hudson Golino <hfg9s@virginia.edu> and Aleksandar Tomasevic <atomashevic@ff.uns.ac.rs>
#' 
#' @importFrom utils packageDescription
#'
"_PACKAGE"
#> [1] "_PACKAGE"