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@@ -23,7 +23,7 @@ This official repository unveils the TransNormerLLM3 model along with its open-s
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  # TransNormerLLM3
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  - **TransNormerLLM3-15B** features **14.83 billion** parameters. It is structured with **42 layers**, includes **40 attention heads**, and has a total **embedding size of 5120**.
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- - **TransNormerLLM3-15B** is purely intergrated with **[Lightning Attention-2](http://arxiv.org/abs/2401.04658)**, which can maintain a stable TGS during training of unlimited sequence lengths, up until encountering firm limitations like GPU memory constraints.
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  - **Titoken** tokenizer is used with a total **vocabulary size** of about **100,000**.
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  - It incorporates **Simple GLU** for its channel mixer, **GLA** in the token mixer, and **SRMSNorm** for normalization.
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  - In terms of position encoding, the first layer employs **LRPE with exponential decay**, whereas the subsequent layers continue with **exponential decay encoding**.
 
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  # TransNormerLLM3
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  - **TransNormerLLM3-15B** features **14.83 billion** parameters. It is structured with **42 layers**, includes **40 attention heads**, and has a total **embedding size of 5120**.
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+ - **TransNormerLLM3-15B** is purely intergrated with **[Lightning Attention-2](http://arxiv.org/abs/2401.04658)**, which can maintain a **stable TGS** during training of **unlimited sequence lengths**, up until encountering firm limitations like GPU memory constraints.
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  - **Titoken** tokenizer is used with a total **vocabulary size** of about **100,000**.
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  - It incorporates **Simple GLU** for its channel mixer, **GLA** in the token mixer, and **SRMSNorm** for normalization.
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  - In terms of position encoding, the first layer employs **LRPE with exponential decay**, whereas the subsequent layers continue with **exponential decay encoding**.