transforEmotion-package: transforEmotion-package

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

transforEmotion–package

Description

Implements sentiment and emotion analysis using huggingface transformer zero-shot classification model pipelines on text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa and default image/video pipeline is Open AI's CLIP. All other zero-shot classification model pipelines can be implemented using their model name from https://huggingface.co/models?pipeline_tag=zero-shot-classification.

Author(s)

Alexander P. Christensen <[e-mail]>, Hudson Golino <[e-mail]> and Aleksandar Tomasevic <[e-mail]>

References

Yin, W., Hay, J., & Roth, D. (2019). Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach. arXiv preprint arXiv:1909.00161.

transforEmotion documentation built on Sept. 11, 2024, 9:26 p.m.