Update README.md

README.md

@@ -76,18 +76,85 @@ Example outputs below.
 - If you use rope to extend context, increase temp AND instructions detail levels to compensate for "rope issues".
 - Source code for this model and Imatrix GGUFs versions will be uploaded shortly at separate repos.
 
-<B>Mixture of Experts Model</b>
+<B>Meet the Team: Mixture of Experts Models</b>
 
-This model is comprised of the following 8 models (in full):
+This model is comprised of the following 8 models ("the experts") (in full):
 
-(coming soon)
+https://huggingface.co/huihui-ai/Llama-3.2-3B-Instruct-abliterated
+
+- https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
+- https://huggingface.co/Hastagaras/L3.2-JametMini-3B-MK.I
+- https://huggingface.co/ValiantLabs/Llama3.2-3B-Enigma
+- https://huggingface.co/Hastagaras/L3.2-JametMini-3B-MK.III
+- https://huggingface.co/huihui-ai/Llama-3.2-3B-Instruct-abliterated
+- https://huggingface.co/chuanli11/Llama-3.2-3B-Instruct-uncensored
+- https://huggingface.co/Lyte/Llama-3.2-3B-Overthinker
+- https://huggingface.co/prithivMLmods/Llama-3.2-3B-Promptist-Mini
 
 The mixture of experts is set at 2 experts, but you can use 3,4,5,6.. 7 and even 8.
 
+You can set the number of experts in LMStudio (https://lmstudio.ai)  at the "load" screen and via other apps/llm apps by setting "Experts" or "Number of Experts".
+
+When using "API", you set the "num_experts_used" in the JSON payload (this maybe different for different back ends).
+
+This "team" has a Captain (first listed model), and then all the team members contribute to the to "token" 
+choice billions of times per second. Note the Captain also contributes too.
+
+Think of 2, 3 or 4 master chefs in the kitchen all competing to make the best dish for you.
+
+This results in higher quality generation.
+
 That means the power of every model is available during instruction and output generation.
 
 This brings unparalleled power to all forms of generation and all use cases.
 
+CREDITS:
+
+Please visit each repo above to see what model(s) contributed to each of models above.
+
+Special credit goes to MERGEKIT, without you this project / model would not have been possible.
+
+[ https://github.com/arcee-ai/mergekit ] 
+
+<B>Special Operations Notes for this MOE model:</B>
+
+Because of how this "MOE" model is configured, even though the default is 2 experts, the "selected" 2 will vary during generation.
+
+(same applies if you change the number of experts used)
+
+This results in vastly different output generation PER generation of each prompt.
+
+This is a positive in terms of variety, but also means it may take 2-4 regens (of the same prompt) to get the highest quality.
+
+In addition, this model responds very well to Dry, Dynamic Temp, and Smooth/Quadratic samplers.
+
+Using these in conjunction with the model can vastly improve output quality.
+
+Higher temps (above 1) can also aid in generation - especially word choice/sentence generation.
+
+When you increase the number of experts used output quality will also increase, at the cost of tokens per second speed.
+
+As you increase/decrease the number of experts, you may want to adjust temp, samplers, and advanced samplers too.
+
+Your quant choice(s) too will impact instruction following and output generation roughly this means the model will understand
+more nuanced instructions and output stronger generation the higher you go up in quant(s).
+
+Quants, Samplers, Generational steering and other topics are covered in the section below:
+
+"Highest Quality Settings..."
+
+<B>Censored / Uncensored / Abliterated:</B>
+
+This model contains several uncensored and/or Abliterated models.
+
+As a result is can output uncensored material.
+
+However there are a few "censored" models which can sometimes interfer, so here is a how to address this:
+
+1 - Regen your prompt a few times.
+
+2 - INCREASE the number of experts used. 
+
 <B>What can I use this model for ?</B>
 
 This model can be used for fiction writing, any creative prose and role play. It can also be used for