Update README.md

README.md

@@ -13,7 +13,7 @@ An experimentation regarding 'lasering' each expert to denoise and enhance model
 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).
 
 
-# Laserxtral - 4x7b (all lasered using laserRMT)
+# Laserxtral - 4x7b (all, except for base, lasered using laserRMT)
 
 This model is a Mixture of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
  * [cognitivecomputations/dolphin-2.6-mistral-7b-dpo](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo)
@@ -22,15 +22,6 @@ This model is a Mixture of Experts (MoE) made with [mergekit](https://github.com
  * [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling)
  * [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
 
-*mlabonne/Marcoro14-7B-slerp (base)
-
-*cognitivecomputations/dolphin-2.6-mistral-7b-dpo
-
-*beowolx/CodeNinja-1.0-OpenChat-7B
-
-*Q-bert/MetaMath-Cybertron-Starling
-
-*WizardLM/WizardMath-7B-V1.1
 
 It follows the implementation of laserRMT @ https://github.com/cognitivecomputations/laserRMT