README.md

---
license: apache-2.0
base_model:
- prithivMLmods/Bootes-Qwen3_Coder-Reasoning
language:
- en
pipeline_tag: text-generation
tags:
- merge
- programming
- code generation
- code
- coding
- coder
- chat
- code
- chat
- brainstorm
- qwen
- qwen3
- qwencoder
- brainstorm20x
library_name: transformers
---

<h2>Qwen3-Bootes-Quick-Coder-Instruct-6B-Brainstorm20x</h2>

This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats.
The source code can also be used directly.

This model contains Brainstorm 20x, combined with prithivMLmods's 4B General / Coder (instruct model):

https://huggingface.co/prithivMLmods/Bootes-Qwen3_Coder-Reasoning

Information on the 4B model below, followed by Brainstorm 20x adapter (by DavidAU) and then a complete help
section for running LLM / AI models.

The Brainstorm adapter improves code generation, and unique code solving abilities.

This model requires:
- Jinja (embedded) or CHATML template
- Max context of 40k.

Settings used for testing (suggested):
- Temp .3 to .7
- Rep pen 1.01 to 1.1  [lower can be better]
- Topp .8 , minp .05
- Topk 20
- No system prompt.

FOR CODING:

Higher temps: .6 to .9 (even over 1) work better for more complex coding / especially with more restrictions.

This model will respond well to both detailed instructions and step by step refinement and additions to code.

As this is an instruct model, it will also benefit from a detailed system prompt too.

For simpler coding problems, lower quants will work well; but for complex/multi-step problem solving suggest Q6 or Q8.

TECH NOTES:

This version was rendered in float16 (instead of bfloat16, native Qwen 3 source). There was in improvement noted
in general model performance by doing this.

Brainstorm, for this model, has removed "reasoning/thinking" blocks for the most part.

This version will produce RAW code directly; with often only "comments" in the code itself.

In otherwords, this model will go directly to "coding" from your prompt bypassing "thinking/reasoning" mode/blocks.

You may want to use this model only for quick / raw coding because without the "thinking" activation, the code
generated is not always top quality.

I strongly suggest the best of 3 generations here for this reason.

See additional suggestions and notes on this model here:

https://huggingface.co/prithivMLmods/Bootes-Qwen3_Coder-Reasoning

---

<B>QUANTS:</b>

---

Special Thanks to Team Mradermacher for the quants:

GGUF:

https://huggingface.co/mradermacher/Qwen3-Bootes-Quick-Coder-Instruct-6B-Brainstorm20x-GGUF

GGUF-IMATRIX:

https://huggingface.co/mradermacher/Qwen3-Bootes-Quick-Coder-Instruct-6B-Brainstorm20x-i1-GGUF

---

<H2>What is Brainstorm?</H2>

---

<B>Brainstorm 20x</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.

What is "Brainstorm" ?

The reasoning center of an LLM is taken apart, reassembled, and expanded.

In this case for this model: 20 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.

---

For more information / other Qwen/Mistral Coders / additional settings see:

[ https://huggingface.co/DavidAU/Qwen2.5-MOE-2x-4x-6x-8x__7B__Power-CODER__19B-30B-42B-53B-gguf ]

---

<H2>Help, Adjustments, Samplers, Parameters and More</H2>

---

<B>CHANGE THE NUMBER OF ACTIVE EXPERTS:</B>

See this document:

https://huggingface.co/DavidAU/How-To-Set-and-Manage-MOE-Mix-of-Experts-Model-Activation-of-Experts

<B>Settings: CHAT / ROLEPLAY and/or SMOOTHER operation of this model:</B>

In "KoboldCpp" or  "oobabooga/text-generation-webui" or "Silly Tavern" ;

Set the "Smoothing_factor" to 1.5 

: in KoboldCpp -> Settings->Samplers->Advanced-> "Smooth_F"

: in text-generation-webui -> parameters -> lower right.

: In Silly Tavern this is called: "Smoothing"


NOTE: For "text-generation-webui" 

-> if using GGUFs you need to use "llama_HF" (which involves downloading some config files from the SOURCE version of this model)

Source versions (and config files) of my models are here:

https://huggingface.co/collections/DavidAU/d-au-source-files-for-gguf-exl2-awq-gptq-hqq-etc-etc-66b55cb8ba25f914cbf210be

OTHER OPTIONS:

- Increase rep pen to 1.1 to 1.15 (you don't need to do this if you use "smoothing_factor")

- If the interface/program you are using to run AI MODELS supports "Quadratic Sampling" ("smoothing") just make the adjustment as noted.

<B>Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers</B>

This a "Class 1" model:

For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) please see:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

You can see all parameters used for generation, in addition to advanced parameters and samplers to get the most out of this model here:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]