Create README.md

README.md

@@ -0,0 +1,235 @@
+---
+license: apache-2.0
+library_name: transformers
+language:
+- en
+- fr
+- zh
+- de
+tags:
+- creative
+- creative writing
+- fiction writing
+- plot generation
+- sub-plot generation
+- fiction writing
+- story generation
+- scene continue
+- storytelling
+- fiction story
+- science fiction
+- romance
+- all genres
+- story
+- writing
+- vivid prose
+- vivid writing
+- moe
+- mixture of experts
+- 128 experts
+- 8 active experts
+- fiction
+- roleplaying
+- bfloat16
+- rp
+- qwen3
+- horror
+- finetune
+- thinking
+- reasoning
+- qwen3_moe
+- uncensored
+- abliterated
+base_model:
+- Qwen/Qwen3-30B-A3B
+pipeline_tag: text-generation
+---
+
+(uploading... ; Quants pending, Examples to be added and model card updates pending...)
+
+<h2>Qwen3-42B-A3B-Stranger-Thoughts-Deep20x-Abliterated-Uncensored</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.
+
+ABOUT:
+
+Qwen's excellent "Qwen3-30B-A3B" with Brainstorm 20x (tech notes at bottom of the page) in a MOE at 42B parameters.
+
+This pushes Qwen's model - abliterated/uncensored to the absolute limit for creative use cases.
+
+Model retains full reasoning, and output generation of a Qwen3 MOE ; but has not been tested for "non-creative" use cases.
+
+Model is set with Qwen's default config:
+- 40 k context
+- 8 of 128 experts activated.
+- Chatml OR Jinja Template (embedded)
+
+ONE example generation below.
+
+USAGE GUIDE:
+
+Please refer to this model card for 
+- Specific usage, suggested settings, changing ACTIVE EXPERTS, templates, settings and the like:
+- How to maximize this model in "uncensored" form, with specific notes on "abliterated" models.
+- Rep pen / temp settings specific to getting the model to perform strongly.
+
+https://huggingface.co/DavidAU/Qwen3-18B-A3B-Stranger-Thoughts-Abliterated-Uncensored-GGUF
+
+---
+
+<H2>EXAMPLES</H2>
+
+Standard system prompt, rep pen 1.05, topk 100, topp .95, minp .05, rep pen range 64.
+
+Tested in LMStudio, quant Q3KS, CPU (GPU output will differ slightly).
+
+As this is the mid range quant, expected better results from higher quants and/or with more experts activated to be better.
+
+NOTE: Some formatting lost on copy/paste.
+
+CAUTION: 
+
+Some horror / intense prose.
+
+---
+
+EXAMPLE #1 - temp 1.2
+
+---
+
+<B>
+</B>
+
+<P></P>
+
+[[[thinking start]]]
+
+[[[thinking end]]]
+
+<p></p>
+
+OUTPUT:
+
+
+
+---
+
+EXAMPLE #2 - temp 1.2
+
+---
+
+<B>
+
+</B>
+
+<P></P>
+
+[[[thinking start]]]
+
+
+[[[thinking end]]]
+
+<p></p>
+
+OUTPUT:
+
+---
+
+EXAMPLE #3 - temp 1.2
+
+---
+
+<B>
+
+</B>
+
+<P></P>
+
+[[[thinking start]]]
+
+
+[[[thinking end]]]
+
+<p></p>
+
+OUTPUT:
+
+---
+
+EXAMPLE #4 - temp 1.2
+
+---
+
+<B>
+
+</B>
+
+<P></P>
+
+[[[thinking start]]]
+
+
+[[[thinking end]]]
+
+<p></p>
+
+OUTPUT:
+
+---
+
+<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.
+
+---