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mradermacher/Qwen2.5-72B-Instruct-abliterated-i1-GGUF

mradermacher Qwen 72B GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 29
  • benchmarks 5 entries
  • hub_downloads_all_time 15,934
  • 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/Qwen2.5-72B-Instruct-abliterated' (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
16K
1K last 30d - cooling
Likes
2
Model age
21mo ago
created 2025-01-11
Downloads over time
Now16.2K→from649↑2,396%
05.9K11.8K17.8K649 on Jan 8, 202516.2K on Oct 11Jan '25Apr '25Jul '25Oct '25JanAprJulOct
Jan 8, 2025 → Oct 11 · 132 snapshots · spans 641 days

Benchmarks

Benchmark Score Source
BBH average 0.6379556362692956 OpenLLM-v2
IFEval instruct 0.8848920863309353 OpenLLM-v2
IFEval-Prompt 0.833641404805915 OpenLLM-v2
MATH lvl 5 0.0037764350453172208 OpenLLM-v2
MMLU-Pro 0.5536901595744681 OpenLLM-v2

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 · 18K downloads combined

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

Metadata

License
other
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
Tags
transformers gguf chat abliterated uncensored zho eng fra spa por deu ita

Related

Total size
633 GB
Files
29
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-04-29 19:38

Files by quantization

Q4_K 2 files 85.0 GB
Qwen2.5-72B-Instruct-abliterated.i1-Q4_K_M.gguf 44.2 GB 542e7f17 download
Qwen2.5-72B-Instruct-abliterated.i1-Q4_K_S.gguf 40.9 GB 8653f1e9 download
Q4 2 files 81.1 GB
Qwen2.5-72B-Instruct-abliterated.i1-Q4_1.gguf 42.6 GB 966aca1f download
Qwen2.5-72B-Instruct-abliterated.i1-Q4_0.gguf 38.5 GB 4ef55224 download
IQ4 1 file 37.0 GB
Qwen2.5-72B-Instruct-abliterated.i1-IQ4_XS.gguf 37.0 GB 4f549132 download
Q3_K 3 files 104 GB
Qwen2.5-72B-Instruct-abliterated.i1-Q3_K_L.gguf 36.8 GB ea6b7929 download
Qwen2.5-72B-Instruct-abliterated.i1-Q3_K_M.gguf 35.1 GB b40acd8d download
Qwen2.5-72B-Instruct-abliterated.i1-Q3_K_S.gguf 32.1 GB 2ca917e9 download
IQ3 4 files 125 GB
Qwen2.5-72B-Instruct-abliterated.i1-IQ3_M.gguf 33.1 GB 77d82299 download
Qwen2.5-72B-Instruct-abliterated.i1-IQ3_S.gguf 32.1 GB 3519af90 download
Qwen2.5-72B-Instruct-abliterated.i1-IQ3_XS.gguf 30.6 GB 8069972a download
Qwen2.5-72B-Instruct-abliterated.i1-IQ3_XXS.gguf 29.7 GB a794bbe0 download
Q2_K 2 files 55.3 GB
Qwen2.5-72B-Instruct-abliterated.i1-Q2_K.gguf 27.8 GB e04f1358 download
Qwen2.5-72B-Instruct-abliterated.i1-Q2_K_S.gguf 27.5 GB 0bb630c0 download
IQ2 4 files 102 GB
Qwen2.5-72B-Instruct-abliterated.i1-IQ2_M.gguf 27.3 GB c31518a5 download
Qwen2.5-72B-Instruct-abliterated.i1-IQ2_S.gguf 26.0 GB 68e19d97 download
Qwen2.5-72B-Instruct-abliterated.i1-IQ2_XS.gguf 25.2 GB 6f5a261e download
Qwen2.5-72B-Instruct-abliterated.i1-IQ2_XXS.gguf 23.7 GB d66b6a6a download
IQ1 2 files 43.2 GB
Qwen2.5-72B-Instruct-abliterated.i1-IQ1_M.gguf 22.1 GB 2cf0e76b download
Qwen2.5-72B-Instruct-abliterated.i1-IQ1_S.gguf 21.1 GB 198f2921 download
Auxiliary files 9 files 159 GB
Qwen2.5-72B-Instruct-abliterated.i1-Q6_K.gguf.part1of2 30.0 GB 21f3f8bf download
Qwen2.5-72B-Instruct-abliterated.i1-Q6_K.gguf.part2of2 29.9 GB af1822cb download
Qwen2.5-72B-Instruct-abliterated.i1-Q5_K_M.gguf.part1of2 26.0 GB b5322029 download
Qwen2.5-72B-Instruct-abliterated.i1-Q5_K_M.gguf.part2of2 24.7 GB 1e783289 download
Qwen2.5-72B-Instruct-abliterated.i1-Q5_K_S.gguf.part1of2 24.0 GB 6e7824c4 download
Qwen2.5-72B-Instruct-abliterated.i1-Q5_K_S.gguf.part2of2 23.8 GB 4f491c88 download
imatrix.dat 24.0 MB 05ea1037 download
README.md 6.59 KB e4eebe60 download
.gitattributes 3.70 KB 79c3bcbb download

README current version from Hugging Face


base_model: huihui-ai/Qwen2.5-72B-Instruct-abliterated
language:


About

weighted/imatrix quants of https://huggingface.co/huihui-ai/Qwen2.5-72B-Instruct-abliterated

static quants are available at https://huggingface.co/mradermacher/Qwen2.5-72B-Instruct-abliterated-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 22.8 for the desperate
GGUF i1-IQ1_M 23.8 mostly desperate
GGUF i1-IQ2_XXS 25.6
GGUF i1-IQ2_XS 27.2
GGUF i1-IQ2_S 28.0
GGUF i1-IQ2_M 29.4
GGUF i1-Q2_K_S 29.7 very low quality
GGUF i1-Q2_K 29.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 31.9 lower quality
GGUF i1-IQ3_XS 32.9
GGUF i1-IQ3_S 34.6 beats Q3_K*
GGUF i1-Q3_K_S 34.6 IQ3_XS probably better
GGUF i1-IQ3_M 35.6
GGUF i1-Q3_K_M 37.8 IQ3_S probably better
GGUF i1-Q3_K_L 39.6 IQ3_M probably better
GGUF i1-IQ4_XS 39.8
GGUF i1-Q4_0 41.5 fast, low quality
GGUF i1-Q4_K_S 44.0 optimal size/speed/quality
GGUF i1-Q4_1 45.8
GGUF i1-Q4_K_M 47.5 fast, recommended
PART 1 PART 2 i1-Q5_K_S 51.5
PART 1 PART 2 i1-Q5_K_M 54.5
PART 1 PART 2 i1-Q6_K 64.4 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.md38567386.6 KB
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  2. 2025-01-12auto-patch README.mdaf216236.5 KB
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  3. 2025-01-12auto-patch README.mdc9966da6.3 KB
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  4. 2025-01-11auto-patch README.md2945a916.2 KB
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  5. 2025-01-11uploaded from nico1f42a2fd250 B
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