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MRockatansky/Gemma-4-31B-Storymaxxed3-GGUF overview

Model Card for Gemma 4 31B storymaxxed3 This model is a fine tuned version of llmfan46/gemma 4 Ortenzya The Creative Wordsmith 31B it uncensored heretic https:…

transformersgguftext-generationdpocreative-writingenarxiv:2305.18290base_model:MRockatansky/Gemma-4-31B-Storymaxxed3base_model:quantized:MRockatansky/Gemma-4-31B-Storymaxxed3license:gemmaendpoints_compatibleregion:usconversational

Runs locally from ~13.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

5 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Gemma-4-31B-Storymaxxed3-F16.ggufGGUFF1657.20 GBDownload
Gemma-4-31B-Storymaxxed3-IQ4_XS.ggufGGUFIQ4_XS15.59 GBDownload
Gemma-4-31B-Storymaxxed3-imatrix-Q4_K_M.ggufGGUFQ4_K_M17.40 GBDownload
mmproj-Storymaxxed3-bf16.ggufGGUFBF161.12 GBDownload
sm3-imatrix.ggufGGUFGGUF13.1 MBDownload

Model Details

Model IDMRockatansky/Gemma-4-31B-Storymaxxed3-GGUF
AuthorMRockatansky
Pipelinetext-generation
Licensegemma
Base modelMRockatansky/Gemma-4-31B-Storymaxxed3
Last modified2026-06-09T05:51:26.000Z

Model README

---

license: gemma

base_model:

  • MRockatansky/Gemma-4-31B-Storymaxxed3

language:

  • en

library_name: transformers

quantized_by: MRockatansky

tags:

  • text-generation
  • dpo
  • creative-writing

---

Model Card for Gemma-4-31B-storymaxxed3

This model is a fine-tuned version of llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic.

It has been trained using TRL. Optimized specifically for creative writing and narrative prose.

The same dataset was used as that for storymaxxed 1 and 2, but with a different base model this time: llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic

along with some tweaks to the training setup.

The first two storymaxxed models needed more writerly prose in my opinion and Ortenzya has excellent word selection and overall just a better writer than stock Gemma-4.

I think it turned out rather well, with good dialogue generation and excellent scene and detail tracking. Equally at home in SFW or NSFW scenarios.

This model should exhibit the same prowess with producing quality stories/narratives with improved prose and better dialogue compared to Storymaxxed 1 and 2.

Training procedure

This model was trained with TRL using DPO on a high quality dataset of narrative preference pairs.

Introduction to training method used:

Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Recommended Sampler Settings

For optimal inference, use the standard generation parameters recommended by Google for Gemma-4 models:

- Temperature - 1.0

- Top P - 0.95

- Top K - 64

Vision mmproj

The mmproj file for vision can be found here: https://huggingface.co/MRockatansky/Gemma-4-31B-Storymaxxed3-GGUF

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