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mradermacher/Qwen2.5-14B-Instruct-abliterated-v2-i1-GGUF

mradermacher Qwen 14B GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 25
  • benchmarks 16 entries
  • hub_downloads_all_time 21,173
  • 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 layer-wise ablation 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='huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2' (base is huihui-ai model (M3))
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
21K
2K last 30d - cooling
Likes
5
Model age
21mo ago
created 2024-12-21
Downloads over time
Now21.6K→from380↑5,572%
07.9K15.8K23.7K380 on Dec 18, 202421.6K on Oct 12Dec '24Mar '25Jun '25Sep '25Dec '25MarJunSep
Dec 18, 2024 → Oct 12 · 138 snapshots · spans 663 days

Benchmarks

Benchmark Score Source
BBH average 0.5638863665845116 OpenLLM-v2
IFEval instruct 0.8633093525179856 OpenLLM-v2
IFEval-Prompt 0.8022181146025879 OpenLLM-v2
MATH lvl 5 0 OpenLLM-v2
MMLU-Pro 0.49617686170212766 OpenLLM-v2
Entertainment 1 UGI
Hazardous 1.8 UGI
Natural Intelligence 19.21 UGI
Political lean -10.8% UGI
Sensitive-Info 17.01 UGI
SocPol 2.5 UGI
UGI 38.84 UGI
Willingness (10) 8.2 UGI
W10-Adherence 8.5 UGI
W10-Direct 8 UGI
Writing 29.12 UGI

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 · 19K downloads combined

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

Metadata

License
apache-2.0
Languages
zho eng fra spa por deu ita rus jpn kor vie tha ara
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf chat abliterated uncensored zho eng fra spa por deu ita

Related

Total size
143 GB
Files
25
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2025-04-29 22:34

Files by quantization

Q6_K 1 file 11.3 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q6_K.gguf 11.3 GB 2d02e7a3 download
Q5_K 2 files 19.3 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q5_K_M.gguf 9.79 GB 84952296 download
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q5_K_S.gguf 9.56 GB 1b560d7c download
Q4_K 2 files 16.4 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q4_K_M.gguf 8.37 GB 551bf024 download
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q4_K_S.gguf 7.98 GB e03a5a5d download
Q4 1 file 7.96 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q4_0.gguf 7.96 GB 728a502d download
IQ4 1 file 7.56 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ4_XS.gguf 7.56 GB 85bdc4ac download
Q3_K 3 files 20.4 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q3_K_L.gguf 7.38 GB d9ecd38a download
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q3_K_M.gguf 6.84 GB 84742e49 download
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q3_K_S.gguf 6.20 GB ca15c4f1 download
IQ3 4 files 24.2 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ3_M.gguf 6.44 GB 76c76327 download
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ3_S.gguf 6.23 GB 88023fa9 download
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ3_XS.gguf 5.94 GB 5ae97efa download
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ3_XXS.gguf 5.54 GB 91a001a2 download
Q2_K 2 files 10.4 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q2_K.gguf 5.37 GB 1cd9bf2f download
Qwen2.5-14B-Instruct-abliterated-v2.i1-Q2_K_S.gguf 5.03 GB 808b563e download
IQ2 4 files 18.0 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ2_M.gguf 4.99 GB b8d8b77f download
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ2_S.gguf 4.66 GB 96b8a20f download
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ2_XS.gguf 4.38 GB 75074184 download
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ2_XXS.gguf 4.02 GB 7861b58d download
IQ1 2 files 6.97 GB
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ1_M.gguf 3.61 GB 76fb3e07 download
Qwen2.5-14B-Instruct-abliterated-v2.i1-IQ1_S.gguf 3.36 GB b65f85d6 download
Auxiliary files 3 files 8.18 MB
imatrix.dat 8.17 MB 044b9927 download
README.md 6.04 KB 217a0413 download
.gitattributes 3.39 KB 11f2b7dc download

README current version from Hugging Face


base_model: huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
language:


About

weighted/imatrix quants of https://huggingface.co/huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2

static quants are available at https://huggingface.co/mradermacher/Qwen2.5-14B-Instruct-abliterated-v2-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 i1-IQ1_S 3.7 for the desperate
GGUF i1-IQ1_M 4.0 mostly desperate
GGUF i1-IQ2_XXS 4.4
GGUF i1-IQ2_XS 4.8
GGUF i1-IQ2_S 5.1
GGUF i1-IQ2_M 5.5
GGUF i1-Q2_K_S 5.5 very low quality
GGUF i1-Q2_K 5.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 6.0 lower quality
GGUF i1-IQ3_XS 6.5
GGUF i1-Q3_K_S 6.8 IQ3_XS probably better
GGUF i1-IQ3_S 6.8 beats Q3_K*
GGUF i1-IQ3_M 7.0
GGUF i1-Q3_K_M 7.4 IQ3_S probably better
GGUF i1-Q3_K_L 8.0 IQ3_M probably better
GGUF i1-IQ4_XS 8.2
GGUF i1-Q4_0 8.6 fast, low quality
GGUF i1-Q4_K_S 8.7 optimal size/speed/quality
GGUF i1-Q4_K_M 9.1 fast, recommended
GGUF i1-Q5_K_S 10.4
GGUF i1-Q5_K_M 10.6
GGUF i1-Q6_K 12.2 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 5 versions

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

  1. 2025-04-29auto-patch README.md729d1406 KB
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  2. 2025-02-09auto-patch README.mdef42c086 KB
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  3. 2025-02-08auto-patch README.md748be735.9 KB
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  4. 2024-12-21auto-patch README.mdf37928c6 KB
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  5. 2024-12-21uploaded from nico1d2ba0a2253 B
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