Update README.md

README.md

@@ -80,71 +80,6 @@ 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 will be uploaded at a separate repo shortly.
 
-<B>Brainstorm 40x</B>
-
-The BRAINSTORM process was developed by David_AU.
-
-Some of the core principals behind this process are discussed in this <a href="https://arxiv.org/pdf/2401.02415"> 
-scientific paper : Progressive LLaMA with Block Expansion </a>. 
-
-However I went in a completely different direction from what was outlined in this paper.
-
-I developed a process where the conclusion layer of a model is duplicated and calibrated, in the case of this model 40 times. 
-
-This is a delicate process, with umm... a lot of rules. 
-
-For this model in particular Brainstorm is mapped as blocks, with "intended disruption" to alter 
-and extend the power of the root model. Each layer/block interacts with each other block.
-
-(there is more going on here too, this is rough summary)
-
-The goal here is creative : prose uniqueness first and foremost.
-
-Other brainstorm methods address logic/problem solving augmentation.
-
-What is "Brainstorm" ?
-
-The reasoning center of an LLM is taken apart, reassembled, and expanded.
-
-In this case for this model: 40 times
-
-Then these centers are individually calibrated. These "centers" also interact with each other. 
-This introduces subtle changes into the reasoning process. 
-The calibrations further adjust - dial up or down - these "changes" further. 
-The number of centers (5x,10x etc) allow more "tuning points" to further customize how the model reasons so to speak.
-
-The core aim of this process is to increase the model's detail, concept and connection to the "world", 
-general concept connections, prose quality and prose length without affecting instruction following. 
-
-This will also enhance any creative use case(s) of any kind, including "brainstorming", creative art form(s) and like case uses.
-
-Here are some of the enhancements this process brings to the model's performance:
-
-- Prose generation seems more focused on the moment to moment. 
-- Sometimes there will be "preamble" and/or foreshadowing present.
-- Fewer or no "cliches"
-- Better overall prose and/or more complex / nuanced prose.
-- A greater sense of nuance on all levels.
-- Coherence is stronger.
-- Description is more detailed, and connected closer to the content.
-- Simile and Metaphors are stronger and better connected to the prose, story, and character.
-- Sense of "there" / in the moment is enhanced.
-- Details are more vivid, and there are more of them.
-- Prose generation length can be long to extreme.
-- Emotional engagement is stronger.
-- The model will take FEWER liberties vs a normal model: It will follow directives more closely but will "guess" less.
-- The MORE instructions and/or details you provide the more strongly the model will respond.
-- Depending on the model "voice" may be more "human" vs original model's "voice".
-
-Other "lab" observations:
-
-- This process does not, in my opinion, make the model 5x or 10x "smarter" - if only that was true! 
-- However, a change in "IQ" was not an issue / a priority, and was not tested or calibrated for so to speak.
-- From lab testing it seems to ponder, and consider more carefully roughly speaking.
-- You could say this process sharpens the model's focus on it's task(s) at a deeper level.
-
-The process to modify the model occurs at the root level - source files level. The model can quanted as a GGUF, EXL2, AWQ etc etc.
-
 <B>Special Operations Notice:</B>
 
 This is a slightly experimental model, and as a result it may "glitch" from time to time - the most common is
@@ -565,3 +500,70 @@ Ishiwa had done his duty. He had sent the message. He had made a difference.
 
 ---
 
+<h2>What is Brainstorm?</h2>
+
+<B>Brainstorm 40x</B>
+
+The BRAINSTORM process was developed by David_AU.
+
+Some of the core principals behind this process are discussed in this <a href="https://arxiv.org/pdf/2401.02415"> 
+scientific paper : Progressive LLaMA with Block Expansion </a>. 
+
+However I went in a completely different direction from what was outlined in this paper.
+
+I developed a process where the conclusion layer of a model is duplicated and calibrated, in the case of this model 40 times. 
+
+This is a delicate process, with umm... a lot of rules. 
+
+For this model in particular Brainstorm is mapped as blocks, with "intended disruption" to alter 
+and extend the power of the root model. Each layer/block interacts with each other block.
+
+(there is more going on here too, this is rough summary)
+
+The goal here is creative : prose uniqueness first and foremost.
+
+Other brainstorm methods address logic/problem solving augmentation.
+
+What is "Brainstorm" ?
+
+The reasoning center of an LLM is taken apart, reassembled, and expanded.
+
+In this case for this model: 40 times
+
+Then these centers are individually calibrated. These "centers" also interact with each other. 
+This introduces subtle changes into the reasoning process. 
+The calibrations further adjust - dial up or down - these "changes" further. 
+The number of centers (5x,10x etc) allow more "tuning points" to further customize how the model reasons so to speak.
+
+The core aim of this process is to increase the model's detail, concept and connection to the "world", 
+general concept connections, prose quality and prose length without affecting instruction following. 
+
+This will also enhance any creative use case(s) of any kind, including "brainstorming", creative art form(s) and like case uses.
+
+Here are some of the enhancements this process brings to the model's performance:
+
+- Prose generation seems more focused on the moment to moment. 
+- Sometimes there will be "preamble" and/or foreshadowing present.
+- Fewer or no "cliches"
+- Better overall prose and/or more complex / nuanced prose.
+- A greater sense of nuance on all levels.
+- Coherence is stronger.
+- Description is more detailed, and connected closer to the content.
+- Simile and Metaphors are stronger and better connected to the prose, story, and character.
+- Sense of "there" / in the moment is enhanced.
+- Details are more vivid, and there are more of them.
+- Prose generation length can be long to extreme.
+- Emotional engagement is stronger.
+- The model will take FEWER liberties vs a normal model: It will follow directives more closely but will "guess" less.
+- The MORE instructions and/or details you provide the more strongly the model will respond.
+- Depending on the model "voice" may be more "human" vs original model's "voice".
+
+Other "lab" observations:
+
+- This process does not, in my opinion, make the model 5x or 10x "smarter" - if only that was true! 
+- However, a change in "IQ" was not an issue / a priority, and was not tested or calibrated for so to speak.
+- From lab testing it seems to ponder, and consider more carefully roughly speaking.
+- You could say this process sharpens the model's focus on it's task(s) at a deeper level.
+
+The process to modify the model occurs at the root level - source files level. The model can quanted as a GGUF, EXL2, AWQ etc etc.
+