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Update README.md

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@@ -8,12 +8,18 @@ An experimentation regarding 'lasering' each expert to denoise and enhance model
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  This model has half size in comparison to the Mixtral 8x7b Instruct. And it basically has the same level of performance (we are working to get a better MMLU score).
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- Used models (all lasered using laserRMT):
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- cognitivecomputations/dolphin-2.6-mistral-7b-dpo
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- mlabonne/Marcoro14-7B-slerp
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- beowolx/CodeNinja-1.0-OpenChat-7B
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- Q-bert/MetaMath-Cybertron-Starling
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- WizardLM/WizardMath-7B-V1.1
 
 
 
 
 
 
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  It follows the implementation of laserRMT @ https://github.com/cognitivecomputations/laserRMT
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  This model has half size in comparison to the Mixtral 8x7b Instruct. And it basically has the same level of performance (we are working to get a better MMLU score).
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+ Used models (all lasered using laserRMT, except for the base model):
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+ *mlabonne/Marcoro14-7B-slerp (base)
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+ *cognitivecomputations/dolphin-2.6-mistral-7b-dpo
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+ *beowolx/CodeNinja-1.0-OpenChat-7B
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+ *Q-bert/MetaMath-Cybertron-Starling
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+ *WizardLM/WizardMath-7B-V1.1
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  It follows the implementation of laserRMT @ https://github.com/cognitivecomputations/laserRMT
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