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transcript-text-analysis

Text Classification
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deberta-v2
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transcript-text-analysis is an encoder model specialized for the classification of French news transcripts. The model is based on debertav3 and has been trained on 1,018 examples of annotated transcripts.

Given a text, transcript-text-analysis will generate the following classifications in French:

  • Emotion (Neutre, Persuasif, Optimiste, Solennel, Alarmant, Indigné)
  • Expression (Interview/Discussion, Publicite, Informations, Meteo, Reportage/Enquete)
  • Intention (Informer, Sensibiliser, Promouvoir, Mobiliser, Divertir, Eduquer)
  • Theme (Santé, Société, Économie, Politique, Sports)
  • Tonalite (Informative, Emotionnelle, Publicitaire)
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