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README.md

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-BERT base (cased) model trained on a subset of 125M tokens of cc100-Swahili for our work [Scaling Laws for BERT in Low-Resource Settings]() at ACL2023 Findings.
+BERT base (cased) model trained on a subset of 125M tokens of cc100-Swahili for our work [Scaling Laws for BERT in Low-Resource Settings](https://aclanthology.org/2023.findings-acl.492.pdf) at ACL2023 Findings.
 
 The model has 124M parameters (12L), and a vocab size of 50K.
 It was trained for 500K steps with a sequence length of 512 tokens and batch-size of 256.