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mradermacher/Qwen2.5-7B-Instruct-abliterated-GGUF

mradermacher Qwen 7B GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 17
  • hub_downloads_all_time 51,676
  • 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/Qwen2.5-7B-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
52K
17K last 30d - stable
Likes
10
Model age
2.1y ago
created 2024-09-20
Downloads over time
Now57.5K→from147↑38,982%
021.1K42.1K63.2K147 on Sep 18, 202457.5K on Oct 11Sep '24Jan '25May '25Sep '25JanMaySep
Sep 18, 2024 → Oct 11 · 148 snapshots · spans 753 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 · 20K 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
F16 IQ3 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf chat abliterated uncensored zho eng fra spa por deu ita

Related

Total size
73.2 GB
Files
17
Quantizations
10
Registered
2026-08-22 13:56
Last updated on HF
2025-04-30 05:22

Files by quantization

F16 1 file 14.2 GB
Qwen2.5-7B-Instruct-abliterated.f16.gguf 14.2 GB 4e1b8cac download
Q8_0 1 file 7.54 GB
Qwen2.5-7B-Instruct-abliterated.Q8_0.gguf 7.54 GB 6282e34f download
Q6_K 1 file 5.82 GB
Qwen2.5-7B-Instruct-abliterated.Q6_K.gguf 5.82 GB 4684dec0 download
Q5_K 2 files 10.0 GB
Qwen2.5-7B-Instruct-abliterated.Q5_K_M.gguf 5.07 GB 0f527c4d download
Qwen2.5-7B-Instruct-abliterated.Q5_K_S.gguf 4.95 GB f6976f13 download
Q4_K 2 files 8.51 GB
Qwen2.5-7B-Instruct-abliterated.Q4_K_M.gguf 4.36 GB 72a55f16 download
Qwen2.5-7B-Instruct-abliterated.Q4_K_S.gguf 4.15 GB e73bc9bb download
IQ4 1 file 3.96 GB
Qwen2.5-7B-Instruct-abliterated.IQ4_XS.gguf 3.96 GB 1d1e9f09 download
Q3_K 3 files 10.6 GB
Qwen2.5-7B-Instruct-abliterated.Q3_K_L.gguf 3.81 GB 497d74fa download
Qwen2.5-7B-Instruct-abliterated.Q3_K_M.gguf 3.55 GB 72e367e3 download
Qwen2.5-7B-Instruct-abliterated.Q3_K_S.gguf 3.25 GB 8e69bd42 download
IQ3 3 files 9.70 GB
Qwen2.5-7B-Instruct-abliterated.IQ3_M.gguf 3.33 GB ec9d9f3b download
Qwen2.5-7B-Instruct-abliterated.IQ3_S.gguf 3.26 GB 0ad5ac42 download
Qwen2.5-7B-Instruct-abliterated.IQ3_XS.gguf 3.12 GB 1c26da66 download
Q2_K 1 file 2.81 GB
Qwen2.5-7B-Instruct-abliterated.Q2_K.gguf 2.81 GB 1e7f7b0d download
Auxiliary files 2 files 6.85 KB
README.md 4.20 KB 2b4e8e80 download
.gitattributes 2.64 KB e04507a5 download

README current version from Hugging Face


base_model: huihui-ai/Qwen2.5-7B-Instruct-abliterated
language:


About

static quants of https://huggingface.co/huihui-ai/Qwen2.5-7B-Instruct-abliterated

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-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 3.1
GGUF IQ3_XS 3.4
GGUF Q3_K_S 3.6
GGUF IQ3_S 3.6 beats Q3_K*
GGUF IQ3_M 3.7
GGUF Q3_K_M 3.9 lower quality
GGUF Q3_K_L 4.2
GGUF IQ4_XS 4.4
GGUF Q4_K_S 4.6 fast, recommended
GGUF Q4_K_M 4.8 fast, recommended
GGUF Q5_K_S 5.4
GGUF Q5_K_M 5.5
GGUF Q6_K 6.4 very good quality
GGUF Q8_0 8.2 fast, best quality
GGUF f16 15.3 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.

README history 3 versions

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

  1. 2025-04-30auto-patch README.mdaf97ac74.2 KB
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  2. 2024-09-20auto-patch README.md1c3076b4.1 KB
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  3. 2024-09-20uploaded from nethype/db12da69b6231 B
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