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mradermacher/Lingshu-32B-abliterated-i1-GGUF

mradermacher 32B GGUF second-order 128K ctx
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Response includes
  • classification m8
  • files 26
  • hub_downloads_all_time 2,444
  • 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='drwlf/Lingshu-32B-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.

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Downloads · lifetime
2K
671 last 30d - stable
Likes
0
Model age
14mo ago
created 2025-07-22
Downloads over time
Now2.6K→from366↑599%
2561.1K1.9K2.8K366 on Jul 23, 20252.6K on Oct 11Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 23, 2025 → Oct 11 · 103 snapshots · spans 445 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 · 925 downloads combined

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

Metadata

Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf en base_model:drwlf/Lingshu-32B-abliterated base_model:quantized:drwlf/Lingshu-32B-abliterated endpoints_compatible region:us imatrix conversational

Related

Total size
327 GB
Files
26
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2025-07-22 07:40

Files by quantization

Q6_K 1 file 25.0 GB
Lingshu-32B-abliterated.i1-Q6_K.gguf 25.0 GB c825928a download
Q5_K 2 files 42.7 GB
Lingshu-32B-abliterated.i1-Q5_K_M.gguf 21.7 GB b4c95a5f download
Lingshu-32B-abliterated.i1-Q5_K_S.gguf 21.1 GB f8d87c54 download
Q4 2 files 36.6 GB
Lingshu-32B-abliterated.i1-Q4_1.gguf 19.2 GB 422034ec download
Lingshu-32B-abliterated.i1-Q4_0.gguf 17.4 GB 0e1d948b download
Q4_K 2 files 36.0 GB
Lingshu-32B-abliterated.i1-Q4_K_M.gguf 18.5 GB d991f67d download
Lingshu-32B-abliterated.i1-Q4_K_S.gguf 17.5 GB eaf463bb download
IQ4 1 file 16.5 GB
Lingshu-32B-abliterated.i1-IQ4_XS.gguf 16.5 GB 7546575a download
Q3_K 3 files 44.3 GB
Lingshu-32B-abliterated.i1-Q3_K_L.gguf 16.1 GB bbe6720f download
Lingshu-32B-abliterated.i1-Q3_K_M.gguf 14.8 GB 5e717245 download
Lingshu-32B-abliterated.i1-Q3_K_S.gguf 13.4 GB ae2a5f1d download
IQ3 4 files 52.0 GB
Lingshu-32B-abliterated.i1-IQ3_M.gguf 13.8 GB 9b9824e1 download
Lingshu-32B-abliterated.i1-IQ3_S.gguf 13.4 GB a0aa153f download
Lingshu-32B-abliterated.i1-IQ3_XS.gguf 12.8 GB 7a141aa4 download
Lingshu-32B-abliterated.i1-IQ3_XXS.gguf 12.0 GB 325dd4d9 download
Q2_K 2 files 22.2 GB
Lingshu-32B-abliterated.i1-Q2_K.gguf 11.5 GB ed6e159b download
Lingshu-32B-abliterated.i1-Q2_K_S.gguf 10.7 GB 61b5e98e download
IQ2 4 files 37.8 GB
Lingshu-32B-abliterated.i1-IQ2_M.gguf 10.5 GB 161c89ba download
Lingshu-32B-abliterated.i1-IQ2_S.gguf 9.67 GB 7da04ba9 download
Lingshu-32B-abliterated.i1-IQ2_XS.gguf 9.27 GB 48201b7e download
Lingshu-32B-abliterated.i1-IQ2_XXS.gguf 8.41 GB dbb01389 download
IQ1 2 files 14.2 GB
Lingshu-32B-abliterated.i1-IQ1_M.gguf 7.39 GB 8543c4eb download
Lingshu-32B-abliterated.i1-IQ1_S.gguf 6.77 GB 0dba76eb download
Auxiliary files 3 files 14.3 MB
imatrix.dat 14.3 MB 9732401d download
README.md 5.74 KB fbff817e download
.gitattributes 3.20 KB 7c45eaf2 download

README current version from Hugging Face


base_model: drwlf/Lingshu-32B-abliterated
language:

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

About

weighted/imatrix quants of https://huggingface.co/drwlf/Lingshu-32B-abliterated

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

static quants are available at https://huggingface.co/mradermacher/Lingshu-32B-abliterated-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

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 i1-IQ1_S 7.4 for the desperate
GGUF i1-IQ1_M 8.0 mostly desperate
GGUF i1-IQ2_XXS 9.1
GGUF i1-IQ2_XS 10.1
GGUF i1-IQ2_S 10.5
GGUF i1-IQ2_M 11.4
GGUF i1-Q2_K_S 11.6 very low quality
GGUF i1-Q2_K 12.4 IQ3_XXS probably better
GGUF i1-IQ3_XXS 12.9 lower quality
GGUF i1-IQ3_XS 13.8
GGUF i1-Q3_K_S 14.5 IQ3_XS probably better
GGUF i1-IQ3_S 14.5 beats Q3_K*
GGUF i1-IQ3_M 14.9
GGUF i1-Q3_K_M 16.0 IQ3_S probably better
GGUF i1-Q3_K_L 17.3 IQ3_M probably better
GGUF i1-IQ4_XS 17.8
GGUF i1-Q4_0 18.8 fast, low quality
GGUF i1-Q4_K_S 18.9 optimal size/speed/quality
GGUF i1-Q4_K_M 20.0 fast, recommended
GGUF i1-Q4_1 20.7
GGUF i1-Q5_K_S 22.7
GGUF i1-Q5_K_M 23.4
GGUF i1-Q6_K 27.0 practically like static Q6_K

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.

README history 2 versions

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

  1. 2025-07-22auto-patch README.md4aff88f5.7 KB
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  2. 2025-07-22uploaded from nico100dde8b237 B
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