Caution: The training for this model is intense enough to alter "real world facts", and bring them in part into the SG1 Universe. V3 is a STRONGER tune, has all 10 seasons and is in float 32/32 bit precison.
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 is specifically for SG1 (Stargate Series), science fiction, story generation (all genres) but also does coding and general tasks too.
This model can also be used for Role play.
Fine tune (4 epochs, using Unsloth for Win 11) on an inhouse generated dataset to simulate / explore the Stargate Universe.
This version has the "canon" of all 10 seasons of SG1.
Fine tune process adds knowledge to the model, and alter all aspects of its operations.
Float32 (32 bit precision) was used to further increase the model's quality.
This model is based on Qwen 3 Instruct 2507 and does NOT have "thinking/reasoning" blocks.
For the reasoning/thinking version go here:
https://huggingface.co/DavidAU/Qwen3-SG1-10S-III-Float32-256k-ctx-6B
Example generations at the bottom of this page.
This is a Stargate (SG1) fine tune (11% of the model, close to 700 million parameters), 4 epochs on this model (a 4B model + Brainstorm 20x adapter)
This model requires:
Settings used for testing (suggested):
As this is an instruct model, it will also benefit from a detailed system prompt too.
QUANTS:
GGUF? GGUF Imatrix? Other?
Special thanks to Team Mradermacher, Team Nightmedia and other quanters!
See under "model tree", upper right and click on "quantizations".
New quants will automatically appear.
CHANGE THE NUMBER OF ACTIVE EXPERTS:
See this document:
https://huggingface.co/DavidAU/How-To-Set-and-Manage-MOE-Mix-of-Experts-Model-Activation-of-Experts
Settings: CHAT / ROLEPLAY and/or SMOOTHER operation of this model:
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:
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.
Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers
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:
You can see all parameters used for generation, in addition to advanced parameters and samplers to get the most out of this model here:
Brainstorm 20x
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.
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:
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.
Example Generation Q4KS , a low/mid level quant - expect better results at higher quants/imatrix etc
IMPORTANT:
Keywords like "SG1" (same for: character names, locations, aliens, enemies, planets IN the SG1 universe ) activate "SG1" mode of operation ; this changes prose, characters, settings, history and so on.
If there are no keywords, directives, system prompt etc etc -> model will perform normally.
