Update README.md

README.md

@@ -3,19 +3,22 @@ license: apache-2.0
 language:
 - en
 library_name: transformers
+tags:
+- moe
 ---
 
 # Aegolius Acadicus 34b v3
 
+MOE model using the Mixtral branch of the mergekit. NOT A MERGE. It is tagged as an moe and is an moe.  It is not a merge of models.
+
 ![img](./aegolius-acadicus.png)
 
-I like to call this model series "The little professor".  I am funding this out of my pocket on rented hardware and runpod to create lora adapters and then assemble MOE models from them and others.  Ultimately I hope to have them all be lora's that I have made.  Whoever took the first one off the leaderboard, I would appreciate it if you would stop.  This is no different than Mixtral and I am working just as hard as the rest of you and spending my own money.  It is simply a MOE merge of lora merged models across Llama2 and Mistral.  I am using this as a test case to move to larger models and get my gate discrimination set correctly.  This model is best suited for knowledge related use cases, I did not give it a specific workload target as I did with some of the other models in the "Owl Series".
+I like to call this model series "The little professor".  I am funding this out of my pocket on rented hardware and runpod to create lora adapters and then assemble MOE models from them and others.  Ultimately I hope to have them all be lora's that I have made.  This is no different than Mixtral and I am literally using their tooling.  It is simply a MOE of lora merged models across Llama2 and Mistral.  I am using this as a test case to move to larger models and get my gate discrimination set correctly.  This model is best suited for knowledge related use cases, I did not give it a specific workload target as I did with some of the other models in the "Owl Series".
 
 In this particular run I am expanding data sets and model count to see if that helps/hurts.  I am also moving to more of my own fine tuned mistrals
 
-I am paying for the fine tunes on runpod myself on these and then merging to larger models to allow them to load as a single model.  Soon I hope to be using entirely models that I have fine tuned myself.
 
-This model is merged from the following sources:
+This model is an moe of the following models:
 
 [Fine Tuned Mistral of Mine](https://huggingface.co/ibivibiv/temp_tuned_mistral2)
 [Fine Tuned Mistral of Mine](https://huggingface.co/ibivibiv/temp_tuned_mistral3)
@@ -24,7 +27,6 @@ This model is merged from the following sources:
 [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2)
 [WestSeverus-7B-DPO](https://huggingface.co/PetroGPT/WestSeverus-7B-DPO)
 
-Unless those models are "contaminated" this one is not.  This is a proof of concept version of this series and you can find others where I am tuning my own models and using moe mergekit to combine them to make moe models that I can run on lower tier hardware with better results.
 
 The goal here is to create specialized models that can collaborate and run as one model.