xlm-emo-t
Detecting emotion in text allows social and computational scientists to study how people behave and react to online events. However, developing these tools for different languages requires data that is not always available. This paper collects the available emotion detection datasets across 19 languages. We train a multilingual emotion prediction model for social media data, XLM-EMO. The model shows competitive perfo...
Params
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Context
512
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Specifications
- Architecture
- XLMRobertaForSequenceClassification
- Context length
- 512
- Vocabulary
- 250,002
- Layers / heads
- 12 / 12
- First seen on the Hub
- 2022-04-06
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any text-classification model