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Les modèles de langue contextuels Camembert pour le Français : impact de la taille et de l'hétérogénéité des données d'entrainement
We explore the impact of the training data size and heterogeneity on French language modeling. (Equal contribution by the first three authors).
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Les modèles de langue contextuels Camembert pour le Français : impact de la taille et de l'hétérogénéité des données d'entrainement
Establishing a New State-of-the-Art for French Named Entity Recognition
We explore convert the NER annotations of the French TreeBank to a more user-friendly format and establish a new state of the art for French NER.
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Establishing a New State-of-the-Art for French Named Entity Recognition
French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus
We investigate the impact of different types and size of training corpora on language models.
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French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus
How OCR Performance can Impact on the Automatic Extraction of Dictionary Content Structures
We explore the impact of the OCR quality on grobid-dictionaries models.
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Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures
We propose a new pipeline to filter, clean and classify Common Crawl by language, we publish the final corpus under the name OSCAR.
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Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures