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transforEmotion: Sentiment Analysis for Text, Image and Video using Transformer Models
Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP <https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.
Getting started
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Package details |
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| Author | Alexander Christensen [aut] (ORCID: <https://orcid.org/0000-0002-9798-7037>), Hudson Golino [aut] (ORCID: <https://orcid.org/0000-0002-1601-1447>), Aleksandar Tomašević [aut, cre] (ORCID: <https://orcid.org/0000-0003-4863-6051>) |
| Maintainer | Aleksandar Tomašević <atomashevic@gmail.com> |
| License | GPL (>= 3.0) |
| Version | 0.1.6 |
| Package repository | View on CRAN |
| Installation |
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