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 ## Model description
 
-This model is a distilled version of [projecte-aina/roberta-base-ca-v2](https://huggingface.co/projecte-aina/roberta-base-ca-v2). It follows the same training procedure as [DistilBERT](https://arxiv.org/abs/1910.01108), using the implementation of Knowledge Distillation from [the paper's repository](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation).
+This model is a distilled version of [projecte-aina/roberta-base-ca-v2](https://huggingface.co/projecte-aina/roberta-base-ca-v2). It follows the same training procedure as [DistilBERT](https://arxiv.org/abs/1910.01108), using the implementation of Knowledge Distillation from the paper's [official repository](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation).
 
 The resulting architecture consists of 6 layers, 768 dimensional embeddings and 12 attention heads, totalizing 82M parameters (compared to 125M parameters of standrard RoBERTa-base models). On average, it is twice as fast as its teacher.