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@@ -35,7 +35,7 @@ Can be run natively and fully offline on phones - try it yourself with [H2O AI P
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  ## Model Architecture
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- We adjust the Llama 2 architecture for a total of around 500m parameters. For details, please refer to our [Technical Report](https://arxiv.org/abs/2401.16818). We use the Mistral tokenizer with a vocabulary size of 32,000 and train our model up to a context length of 8,192.
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  The details of the model architecture are:
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  ## Model Architecture
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+ We adjust the Llama 2 architecture for a total of around 500m parameters. For details, please refer to our [Technical Report](https://arxiv.org/abs/2407.09276). We use the Mistral tokenizer with a vocabulary size of 32,000 and train our model up to a context length of 8,192.
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  The details of the model architecture are:
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