StyleTune V2 finetune converted to GGUF and quantized with an unofficial reapplication of the PRISM-PRO-DQ per-tensor type map.
Important provenance notice
This is not an official PRISM-DQ or PRISM-PRO-DQ model. This repository is not affiliated with Ex0bit, PRISM-DQ, or the authors of the source finetune.
The underlying trained weights come from Gryphe/Gemma-4-26B-A4B-StyleTune-V2. No trained tensor values from Ex0bit's PRISM model were copied, merged, or transplanted into this model.
The quantized file was produced by reconstructing the per-tensor GGML quantization-type assignment visible in the public Ex0bit/Gemma4-26B-A4B-PRISM-PRO-DQ-GGUF release and then applying that assignment to this separate finetune. This is therefore a map reapplication, not a reproduction of the original PRISM-DQ calibration, optimization procedure, dataset, or proprietary pipeline.
The Unsloth importance matrix imatrix_unsloth.gguf_file was used during quantization. Conversion and quantization were performed with llama.cpp.
Quantization layout
For the 658 tensors shared with the reference Gemma 4 PRISM-PRO-DQ GGUF, the final distribution is:
GGML type
Tensor count
F32
392
Q5_1
30
Q5_K
91
Q6_K
115
Q8_0
30
This source checkpoint contains a separate output.weight, resulting in 659 tensors. That tensor was preserved and stored as Q5_K rather than discarded or tied during conversion.
This GGUF embeds temperature = 1.0, top_p = 0.95, and top_k = 64. It does not embed min_p = 0.10 or the DRY sampler configuration, so those two settings must be selected manually in the inference frontend or passed through the corresponding llama.cpp options.
Use of this repository remains subject to the original source model's license and the Gemma Terms of Use. The behavior and safety characteristics of the source finetune are inherited; quantization does not make the model safer or change its intended-use restrictions. Users are responsible for evaluating outputs and complying with applicable laws and licenses.
