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mradermacher/Qwen2-VL-72B-Instruct-abliterated-GGUF

mradermacher Qwen 72B GGUF multimodal second-order 33K ctx
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Response includes
  • classification m8
  • files 18
  • hub_downloads_all_time 4,084
  • 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-VL-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
4K
480 last 30d - stable
Likes
0
Model age
22mo ago
created 2024-12-15
Downloads over time
Now4.4K→from40↑10,908%
01.6K3.2K4.8K40 on Dec 11, 20244.4K on Oct 114.4K on Oct 10Dec '24Mar '25Jun '25Sep '25Dec '25MarJunSep
Dec 11, 2024 → Oct 11 · 135 snapshots · spans 669 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 · 901 downloads combined

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

Metadata

License
other
Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K
Tags
transformers gguf abliterated uncensored multimodal en license:other endpoints_compatible region:us conversational

Related

Total size
254 GB
Files
18
Quantizations
6
Registered
2026-08-22 13:56
Last updated on HF
2025-08-01 00:48

Files by quantization

Q4_K 2 files 85.0 GB
Qwen2-VL-72B-Instruct-abliterated.Q4_K_M.gguf 44.2 GB 4fa7a3fe download
Qwen2-VL-72B-Instruct-abliterated.Q4_K_S.gguf 40.9 GB ce58c546 download
IQ4 1 file 37.4 GB
Qwen2-VL-72B-Instruct-abliterated.IQ4_XS.gguf 37.4 GB 9fbae418 download
Q3_K 3 files 104 GB
Qwen2-VL-72B-Instruct-abliterated.Q3_K_L.gguf 36.8 GB 0673e3f3 download
Qwen2-VL-72B-Instruct-abliterated.Q3_K_M.gguf 35.1 GB 6a02916f download
Qwen2-VL-72B-Instruct-abliterated.Q3_K_S.gguf 32.1 GB 0a28afeb download
Q2_K 1 file 27.8 GB
Qwen2-VL-72B-Instruct-abliterated.Q2_K.gguf 27.8 GB 93829c7c download
F16 1 file 1.30 GB
Qwen2-VL-72B-Instruct-abliterated.mmproj-fp16.gguf 1.30 GB 54a317af download
Auxiliary files 10 files 230 GB
Qwen2-VL-72B-Instruct-abliterated.Q8_0.gguf.part1of2 36.0 GB 84dd25aa download
Qwen2-VL-72B-Instruct-abliterated.Q8_0.gguf.part2of2 36.0 GB 957f1070 download
Qwen2-VL-72B-Instruct-abliterated.Q6_K.gguf.part1of2 30.0 GB 2da14451 download
Qwen2-VL-72B-Instruct-abliterated.Q6_K.gguf.part2of2 29.9 GB 5924b553 download
Qwen2-VL-72B-Instruct-abliterated.Q5_K_M.gguf.part1of2 26.0 GB 90142368 download
Qwen2-VL-72B-Instruct-abliterated.Q5_K_M.gguf.part2of2 24.7 GB 76fe0ec3 download
Qwen2-VL-72B-Instruct-abliterated.Q5_K_S.gguf.part1of2 24.0 GB 48c6c9dd download
Qwen2-VL-72B-Instruct-abliterated.Q5_K_S.gguf.part2of2 23.8 GB 985de7a9 download
README.md 4.59 KB 54d0d40e download
.gitattributes 2.83 KB 5db22990 download

README current version from Hugging Face


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


About

static quants of https://huggingface.co/huihui-ai/Qwen2-VL-72B-Instruct-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/Qwen2-VL-72B-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 mmproj-fp16 1.5 multi-modal supplement
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 6 versions

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

  1. 2025-08-01auto-patch README.mdfd1c1464.6 KB
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  2. 2025-06-01auto-patch README.md17456d04.6 KB
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  3. 2025-01-21auto-patch README.mdfe7faf74.6 KB
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  4. 2024-12-15auto-patch README.md45938054.4 KB
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  5. 2024-12-15auto-patch README.md4ae961d3.8 KB
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  6. 2024-12-15uploaded from nico1036df6e233 B
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Discussions 1 thread

  1. 2024-12-17no metadata for mergingclosed2 💬#1
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