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mradermacher/command-a-03-2025-writer-v1-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…

transformersggufenfrdeesitptjakozharelfaplidcshehinlrorutruk

Runs locally from ~39.23 GB disk (32 GB+ VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
command-a-03-2025-writer-v1.Q2_K.ggufGGUFGGUF39.23 GBDownload
command-a-03-2025-writer-v1.Q3_K_S.ggufGGUFGGUF45.60 GBDownload

Model Details

Model IDmradermacher/command-a-03-2025-writer-v1-GGUF
Authormradermacher
Pipeline—
Licensecc-by-nc-4.0
Base modeljukofyork/command-a-03-2025-writer-v1
Last modified2026-10-15T21:09:06.000Z

Model README

---

base_model: jukofyork/command-a-03-2025-writer-v1

datasets:

  • jukofyork/books-fiction-paragraphs
  • jukofyork/slop-fiction-paragraphs

language:

  • en
  • fr
  • de
  • es
  • it
  • pt
  • ja
  • ko
  • zh
  • ar
  • el
  • fa
  • pl
  • id
  • cs
  • he
  • hi
  • nl
  • ro
  • ru
  • tr
  • uk
  • vi

library_name: transformers

license: cc-by-nc-4.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

---

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/jukofyork/command-a-03-2025-writer-v1

<!-- 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/command-a-03-2025-writer-v1-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 | 42.2 | |

| GGUF | Q3_K_S | 49.1 | |

| PART 1 PART 2 | Q3_K_M | 54.5 | lower quality |

| PART 1 PART 2 | Q3_K_L | 59.2 | |

| PART 1 PART 2 | IQ4_XS | 60.7 | |

| PART 1 PART 2 | Q4_K_S | 63.9 | fast, recommended |

| PART 1 PART 2 | Q4_K_M | 67.2 | fast, recommended |

| PART 1 PART 2 | Q5_K_S | 76.9 | |

| PART 1 PART 2 | Q5_K_M | 78.9 | |

| PART 1 PART 2 | Q6_K | 91.2 | very good quality |

| PART 1 PART 2 PART 3 | Q8_0 | 118.1 | 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. 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.

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