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hammerai/MN-Violet-Lotus-12B-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: static quants of https://huggingface.co/FallenMerick/MN Viole…

transformersggufstorywritingtext adventurecreativestorywritingfictionroleplayingrpmergekitmergeenbase_model:FallenMerick/MN-Violet-Lotus-12Bbase_model:quantized:FallenMerick/MN-Violet-Lotus-12Blicense:cc-by-4.0endpoints_compatibleregion:usconversational

Runs locally from ~6.96 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

3 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
MN-Violet-Lotus-12B.Q4_K_M.ggufGGUFGGUF6.96 GBDownload
MN-Violet-Lotus-12B.Q6_K.ggufGGUFGGUF9.37 GBDownload
MN-Violet-Lotus-12B.Q8_0.ggufGGUFGGUF12.13 GBDownload

Model Details

Model IDhammerai/MN-Violet-Lotus-12B-GGUF
Authorhammerai
Pipeline
Licensecc-by-4.0
Base modelFallenMerick/MN-Violet-Lotus-12B
Last modified2026-07-01T02:10:47.000Z

Model README

---

base_model: FallenMerick/MN-Violet-Lotus-12B

language:

  • en

library_name: transformers

license: cc-by-4.0

quantized_by: mradermacher

tags:

  • storywriting
  • text adventure
  • creative
  • story
  • writing
  • fiction
  • roleplaying
  • rp
  • mergekit
  • merge

---

About

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

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

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

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

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

static quants of https://huggingface.co/FallenMerick/MN-Violet-Lotus-12B

<!-- provided-files -->

weighted/imatrix quants are available at https://huggingface.co/mradermacher/MN-Violet-Lotus-12B-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 | Q2_K | 4.9 | |

| GGUF | Q3_K_S | 5.6 | |

| GGUF | Q3_K_M | 6.2 | lower quality |

| GGUF | Q3_K_L | 6.7 | |

| GGUF | IQ4_XS | 6.9 | |

| GGUF | Q4_0_4_4 | 7.2 | fast on arm, low quality |

| GGUF | Q4_K_S | 7.2 | fast, recommended |

| GGUF | Q4_K_M | 7.6 | fast, recommended |

| GGUF | Q5_K_S | 8.6 | |

| GGUF | Q5_K_M | 8.8 | |

| GGUF | Q6_K | 10.2 | very good quality |

| GGUF | Q8_0 | 13.1 | fast, best quality |

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.

<!-- end -->

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