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@@ -45,7 +45,7 @@ Our final vocab file availabe at [https://github.com/sagorbrur/bangla-bert](http
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  * Bangla-Bert was trained with code provided in Google BERT's github repository (https://github.com/google-research/bert)
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  * Currently released model follows bert-base-uncased model architecture (12-layer, 768-hidden, 12-heads, 110M parameters)
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  * Total Training Steps: 1 Million
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- * The model was trained on a single Google Cloud TPU
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  ## Evaluation Results
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@@ -142,6 +142,11 @@ for pred in nlp(f"আমি বাংলায় {nlp.tokenizer.mask_token} গা
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  ## Reference
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  * https://github.com/google-research/bert
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  ## Citation
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  If you find this model helpful, please cite.
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  * Bangla-Bert was trained with code provided in Google BERT's github repository (https://github.com/google-research/bert)
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  * Currently released model follows bert-base-uncased model architecture (12-layer, 768-hidden, 12-heads, 110M parameters)
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  * Total Training Steps: 1 Million
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+ * The model was trained on a single Google Cloud GPU
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  ## Evaluation Results
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  ## Reference
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  * https://github.com/google-research/bert
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+ ## Acknowledgements
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+
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+ * Thanks to Google [TensorFlow Research Cloud (TFRC)](https://www.tensorflow.org/tfrc) for providing the free GPU credits - thank you!
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+ * Thank to all the people around, who always helping us to build something for Bengali.
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+
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  ## Citation
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  If you find this model helpful, please cite.
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