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mradermacher/gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: < quants: x f16 Q4 K S Q2 K Q8 0 Q6 K Q3 K M Q3 K S Q3 K L Q4…

transformersggufhereticuncensoredaliteratedfinetuneunslothall use casescodercreativecreative writingfiction writingplot generationsub-plot generationstory generationscene continuestorytellingfiction storyscience fictionromanceall genresstorywritingvivid prosing

Runs locally from ~531.5 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Pipeline
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Repository Files & Downloads

14 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.IQ4_XS.ggufGGUFGGUF3.08 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q2_K.ggufGGUFGGUF2.78 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q3_K_L.ggufGGUFGGUF3.06 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q3_K_M.ggufGGUFGGUF2.98 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q3_K_S.ggufGGUFGGUF2.90 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q4_K_M.ggufGGUFGGUF3.19 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q4_K_S.ggufGGUFGGUF3.13 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q5_K_M.ggufGGUFGGUF3.38 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q5_K_S.ggufGGUFGGUF3.35 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q6_K.ggufGGUFGGUF3.58 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.Q8_0.ggufGGUFGGUF4.63 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.f16.ggufGGUFGGUF8.67 GBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.mmproj-Q8_0.ggufGGUFQ8_0531.5 MBDownload
gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking.mmproj-f16.ggufGGUFF16940.0 MBDownload

Model Details

Model IDmradermacher/gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking-GGUF
Authormradermacher
Pipeline—
Licenseapache-2.0
Base modelDavidAU/gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking
Last modified2026-10-13T21:48:17.000Z

Model README

---

base_model: DavidAU/gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • heretic
  • uncensored
  • aliterated
  • finetune
  • unsloth
  • finetune
  • all use cases
  • coder
  • creative
  • creative writing
  • fiction writing
  • plot generation
  • sub-plot generation
  • fiction writing
  • story generation
  • scene continue
  • storytelling
  • fiction story
  • science fiction
  • romance
  • all genres
  • story
  • writing
  • vivid prosing
  • vivid writing
  • fiction
  • roleplaying
  • bfloat16
  • all use cases

---

About

<!-- ### quantize_version: 2 -->

<!-- ### output_tensor_quantised: 1 -->

<!-- ### convert_type: hf -->

<!-- ### vocab_type: -->

<!-- ### tags: -->

<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: -->

static quants of https://huggingface.co/DavidAU/gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking

<!-- provided-files -->

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/gemma-4-E2B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's

READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for

more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes |

|:-----|:-----|--------:|:------|

| GGUF | mmproj-Q8_0 | 0.7 | multi-modal supplement |

| GGUF | mmproj-f16 | 1.1 | multi-modal supplement |

| GGUF | Q2_K | 3.1 | |

| GGUF | Q3_K_S | 3.2 | |

| GGUF | Q3_K_M | 3.3 | lower quality |

| GGUF | Q3_K_L | 3.4 | |

| GGUF | IQ4_XS | 3.4 | |

| GGUF | Q4_K_S | 3.5 | fast, recommended |

| GGUF | Q4_K_M | 3.5 | fast, recommended |

| GGUF | Q5_K_S | 3.7 | |

| GGUF | Q5_K_M | 3.7 | |

| GGUF | Q6_K | 3.9 | very good quality |

| GGUF | Q8_0 | 5.1 | fast, best quality |

| GGUF | f16 | 9.4 | 16 bpw, overkill |

Here is a handy graph by ikawrakow comparing some lower-quality quant

types (lower is better):

!image.png

And here are Artefact2's thoughts on the matter:

https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to

questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting

me use its servers and providing upgrades to my workstation to enable

this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

<!-- end -->

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