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mradermacher/Bielik-Minitron-7B-v3.0-Instruct-heretic-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…

transformersggufhereticuncensoreddecensoredabliteratedreproduciblemultilingualplensqbelbsbghrcsdaetfifrelesislt

Runs locally from ~2.62 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

12 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Bielik-Minitron-7B-v3.0-Instruct-heretic.IQ4_XS.ggufGGUFGGUF3.79 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q2_K.ggufGGUFGGUF2.62 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q3_K_L.ggufGGUFGGUF3.69 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q3_K_M.ggufGGUFGGUF3.39 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q3_K_S.ggufGGUFGGUF3.04 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q4_K_M.ggufGGUFGGUF4.19 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q4_K_S.ggufGGUFGGUF3.98 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q5_K_M.ggufGGUFGGUF4.93 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q5_K_S.ggufGGUFGGUF4.81 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q6_K.ggufGGUFGGUF5.71 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.Q8_0.ggufGGUFGGUF7.40 GBDownload
Bielik-Minitron-7B-v3.0-Instruct-heretic.f16.ggufGGUFGGUF13.93 GBDownload

Model Details

Model IDmradermacher/Bielik-Minitron-7B-v3.0-Instruct-heretic-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelpiotreknow02/Bielik-Minitron-7B-v3.0-Instruct-heretic
Last modified2026-07-09T12:14:24.000Z

Model README

---

base_model: piotreknow02/Bielik-Minitron-7B-v3.0-Instruct-heretic

extra_gated_fields:

I agree to be contacted for feedback about Bielik models: checkbox

language:

  • multilingual
  • pl
  • en
  • sq
  • bel
  • bs
  • bg
  • hr
  • cs
  • da
  • et
  • fi
  • fr
  • el
  • es
  • is
  • lt
  • nl
  • de
  • no
  • pt
  • ru
  • ro
  • sr
  • hbs
  • sv
  • sk
  • sl
  • tr
  • uk
  • hu
  • it
  • lv

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • heretic
  • uncensored
  • decensored
  • abliterated
  • reproducible

---

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/piotreknow02/Bielik-Minitron-7B-v3.0-Instruct-heretic

<!-- 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/Bielik-Minitron-7B-v3.0-Instruct-heretic-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 | 2.9 | |

| GGUF | Q3_K_S | 3.4 | |

| GGUF | Q3_K_M | 3.7 | lower quality |

| GGUF | Q3_K_L | 4.1 | |

| GGUF | IQ4_XS | 4.2 | |

| GGUF | Q4_K_S | 4.4 | fast, recommended |

| GGUF | Q4_K_M | 4.6 | fast, recommended |

| GGUF | Q5_K_S | 5.3 | |

| GGUF | Q5_K_M | 5.4 | |

| GGUF | Q6_K | 6.2 | very good quality |

| GGUF | Q8_0 | 8.0 | fast, best quality |

| GGUF | f16 | 15.1 | 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.

<!-- end -->

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