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@@ -36,7 +36,7 @@ State of the art, small language model pretrained from scratch on a diverse set
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  ## Details
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- We used the revision on step 900,000 for evaluations which trained for ~12 on an RTX PRO 6000. It trained on 131.69 billion bytes which is between 32.92B and 43.90B standard tokens, around ~38 billion bpe tokens on average. For more details on the evals and inference, please have a look at the [official notebook](https://huggingface.co/dotlabs/void.1/blob/main/evals.ipynb).
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  ```bibtex
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  @misc{dotlabs,
 
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  ## Details
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+ We used the revision on step 900,000 for evaluations which trained for ~12 days on a single RTX PRO 6000 gpu. It trained on 131.69 billion bytes which is between 32.92B and 43.90B standard tokens, around ~38 billion bpe tokens on average. For more details on the evals and inference, please have a look at the [official notebook](https://huggingface.co/dotlabs/void.1/blob/main/evals.ipynb).
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  ```bibtex
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  @misc{dotlabs,