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mradermacher/Medguide-V_0723-abliterated-GGUF

mradermacher GGUF second-order 128K ctx
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Response includes
  • classification m8
  • files 17
  • hub_downloads_all_time 248
  • author_summary 3324 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=mradermacher (M8 quantization producer, never originator)
  • is_gguf=1
  • base_model='nicoboss/Medguide-V_0723-abliterated' (base has 'abliterated' marker, assume M1 default)
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
248
171 last 30d - active
Likes
0
Model age
14mo ago
created 2025-07-26
Downloads over time
Now278→from87↑220%
010220430687 on Jul 30, 2025278 on Oct 11278 on Dec 10, 2025Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 30, 2025 → Oct 11 · 102 snapshots · spans 438 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 562 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K
Tags
transformers gguf en base_model:nicoboss/Medguide-V_0723-abliterated base_model:quantized:nicoboss/Medguide-V_0723-abliterated endpoints_compatible region:us conversational

Related

Total size
254 GB
Files
17
Quantizations
5
Registered
2026-08-22 13:56
Last updated on HF
2025-07-31 02:21

Files by quantization

Q4_K 2 files 85.0 GB
Medguide-V_0723-abliterated.Q4_K_M.gguf 44.2 GB 1625cd61 download
Medguide-V_0723-abliterated.Q4_K_S.gguf 40.9 GB b8611f78 download
IQ4 1 file 37.4 GB
Medguide-V_0723-abliterated.IQ4_XS.gguf 37.4 GB ece22264 download
Q3_K 3 files 104 GB
Medguide-V_0723-abliterated.Q3_K_L.gguf 36.8 GB baf41903 download
Medguide-V_0723-abliterated.Q3_K_M.gguf 35.1 GB bfc00da5 download
Medguide-V_0723-abliterated.Q3_K_S.gguf 32.1 GB b1cdae5a download
Q2_K 1 file 27.8 GB
Medguide-V_0723-abliterated.Q2_K.gguf 27.8 GB e7e359eb download
Auxiliary files 10 files 230 GB
Medguide-V_0723-abliterated.Q8_0.gguf.part1of2 36.0 GB 574cac7c download
Medguide-V_0723-abliterated.Q8_0.gguf.part2of2 36.0 GB 49d23449 download
Medguide-V_0723-abliterated.Q6_K.gguf.part1of2 30.0 GB 6bfacd64 download
Medguide-V_0723-abliterated.Q6_K.gguf.part2of2 29.9 GB fd8caabc download
Medguide-V_0723-abliterated.Q5_K_M.gguf.part1of2 26.0 GB f5fd50ff download
Medguide-V_0723-abliterated.Q5_K_M.gguf.part2of2 24.7 GB f41b05c2 download
Medguide-V_0723-abliterated.Q5_K_S.gguf.part1of2 24.0 GB c8f60c0f download
Medguide-V_0723-abliterated.Q5_K_S.gguf.part2of2 23.8 GB 8ca1ae4a download
README.md 4.16 KB eb9aea5d download
.gitattributes 2.66 KB fbb2eab5 download

README current version from Hugging Face


base_model: nicoboss/Medguide-V_0723-abliterated
language:

  • en
    library_name: transformers
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher

About

static quants of https://huggingface.co/nicoboss/Medguide-V_0723-abliterated

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Medguide-V_0723-abliterated-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs
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 29.9
GGUF Q3_K_S 34.6
GGUF Q3_K_M 37.8 lower quality
GGUF Q3_K_L 39.6
GGUF IQ4_XS 40.3
GGUF Q4_K_S 44.0 fast, recommended
GGUF Q4_K_M 47.5 fast, recommended
PART 1 PART 2 Q5_K_S 51.5
PART 1 PART 2 Q5_K_M 54.5
PART 1 PART 2 Q6_K 64.4 very good quality
PART 1 PART 2 Q8_0 77.4 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.

README history 4 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2025-07-31auto-patch README.md3f5402f4.2 KB
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  2. 2025-07-26auto-patch README.mde46af9a4.4 KB
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  3. 2025-07-26auto-patch README.md2bcbe2f4 KB
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  4. 2025-07-26uploaded from nico1dac8d0b378 B
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