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@@ -8,7 +8,7 @@ license: apache-2.0
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  <img src="elm-rambutan.png" width="256"/>
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- ELM is designed to be a modular and customizable family of neural networks that are highly efficient and performant. Today we are sharing the first version in this series: **ELM-v0.1** models.
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  _Model:_ ELM introduces a new type of _(de)-composable LLM model architecture_ along with the algorithmic optimizations required to learn (training) and run (inference) these models. At a high level, we train a single ELM model in a self-supervised manner (during pre-training phase) but once trained the ELM model can be sliced in many ways to fit different user/task needs. The optimizations can be applied to the model either during the pre-training and/or fine-tuning stage.
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  <img src="elm-rambutan.png" width="256"/>
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  </div>
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+ ELM is designed to be a modular and customizable family of neural networks that are highly efficient and performant. Today we are sharing the first version in this series: **ELM-v0.1** models (named _Rambutan_).
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  _Model:_ ELM introduces a new type of _(de)-composable LLM model architecture_ along with the algorithmic optimizations required to learn (training) and run (inference) these models. At a high level, we train a single ELM model in a self-supervised manner (during pre-training phase) but once trained the ELM model can be sliced in many ways to fit different user/task needs. The optimizations can be applied to the model either during the pre-training and/or fine-tuning stage.
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