This repo contains quants 4x of L3-SthenoMaidBlackroot-8B-V1 (now at 10.4B) using the "Brainstorm" method of augmenting reasoning in a LLM to increase it's performance at the core level for ANY creative use case(s).
This version has 4 "reasoning" centers - one from the original merge, and 3 from the unmerged models (at close to full strength) melded into a 4 layer reasoning center. Each of these reasoning centers is further split into 3 units and also calibrated for a total of 12 "reasoning centers".
The BRAINSTORM process was developed by David_AU.
Some of the core principals behind this process are discussed in this scientific paper : Progressive LLaMA with Block Expansion . 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.
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 (4x,5x,8x,10x etc) allow more "tuning points" to further customize how the model reasons so to speak.
The "Multi" reasoning system pulls "reasoning centers" from multiple models and fuses these into one long "chain of reasoning" so to speak. Each one is then calibrated. Each "center" interacts with the other "centers" and the order of the centers further impacts the model's output style - again roughly speaking.
Each of these is further split, expanded and calibrated.
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:
Other "lab" observations:
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.
Other technologies developed by David_AU like "Ultra" (precision), "Neo Imatrix" (custom imatrix datasets), and "X-quants" (custom application of the imatrix process) can further enhance the performance of the model along with the "Brainstorm" process.
The "Brainstorm" process has been tested on multiple LLama2, Llama3, and Mistral models of various parameter sizes, as well as on "root" models like "Llama3 Instruct", "Mistral Instruct", and "merged" / "fine tuned" models too.
Usage Notice:
You may need to raise the "repeat penalty" from a default of 1.1 to slightly higher levels in some use case(s).
Original Model:
For original model specifications, usage information and other important details please see:
[ https://huggingface.co/DavidAU/L3-8B-Stheno-v3.2-Ultra-NEO-V1-IMATRIX-GGUF ]
and the original model page:
Special thanks to the model creators at SAO10K for making such a fantastic model:
[ https://huggingface.co/Sao10K/L3-8B-Stheno-v3.2 ]
Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers
This a "Class 2" 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:
You can see all parameters used for generation, in addition to advanced parameters and samplers to get the most out of this model here:
