The goal was a small, practical creative/voice/writing model that keeps more coherence than a plain Q4-style quant while still fitting comfortably on modest GPUs. The storyMaker name reflects the actual niche where it stood out: expressive writing, roleplay, voice-adjacent prose, and creative instruction following.
This was an unplanned release. The author was testing models for creative writing use, found a quantized GGUF of this model that showed severe looping and quality degradation, and built this version to check whether the issue came from the core finetune or from the quantization. The result was unexpectedly useful: creative, able to reason, good at following instructions, strong for roleplay, and expressive in a way that made it enjoyable to use. Because of that, it was uploaded for anyone else interested in this niche.
Because this was exploratory rather than a planned release, it has not gone through the author's usual comprehensive release process. A gender-affirming finetune based on the DavidAU model may come later for people interested in that direction.
What Is Special
This is not a plain one-shot Q4 quant.
The released GGUF is:
base quant: IQ4_NL
calibration: English creative writing, general logic, emotional understanding, and voice/vocal-concept prompts
imatrix: 1000 calibration chunks at ctx512, 342 importance-matrix entries
protected tensors: attention q, k, v, and output projections in blocks 36..41
protected quant type: Q8_0
In other words, most of the model stays Q4-sized, while the final six attention blocks are kept at higher precision. The intent is to spend a small amount of extra size on the late attention path, where coherence, style continuity, and repetition stability are more likely to matter for writing-style use.
The included no-thinking template is optional, but it is the one we used for the creative deployment. The upstream model is a thinking model, and in our creative tests the no-thinking template reduced scaffold-style answers.
This quant was tuned for English creative writing, expressive prose, conceptual writing, emotional/voice-adjacent discussion, and general reasoning. It was not built as a coding specialist.
Because the source model is an uncensored/aliterated model, apply your own safety, policy, and deployment filters where needed.
