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mradermacher/BigBang-Aquila-35B-Merged-Abliterated-GGUF

mradermacher 35B GGUF MoE second-order 262K ctx
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Response includes
  • classification m8
  • files 13
  • hub_downloads_all_time 4,959
  • 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='osk-arr00/BigBang-Aquila-35B-Merged-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
5K
4K last 30d - active
Likes
0
Model age
7w ago
created 2026-08-21
Downloads over time
Now5K→from196↑2,470%
01.8K3.7K5.5K196 on Aug 195K on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 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 · 10K downloads combined

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

Metadata

License
apache-2.0
Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf safetensors qwen3_5_moe merge abliterated uncensored en base_model:Davd-b01/BigBang-Aquila-35B-Merged-Abliterated base_model:quantized:Davd-b01/BigBang-Aquila-35B-Merged-Abliterated license:apache-2.0 endpoints_compatible

Related

Total size
221 GB
Files
13
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2026-09-08 13:37

Files by quantization

Q8_0 1 file 34.4 GB
BigBang-Aquila-35B-Merged-Abliterated.Q8_0.gguf 34.4 GB bd1923ac download
Q6_K 1 file 26.6 GB
BigBang-Aquila-35B-Merged-Abliterated.Q6_K.gguf 26.6 GB 11804357 download
Q5_K 2 files 45.4 GB
BigBang-Aquila-35B-Merged-Abliterated.Q5_K_M.gguf 23.0 GB 1273c213 download
BigBang-Aquila-35B-Merged-Abliterated.Q5_K_S.gguf 22.3 GB 5dc53b73 download
Q4_K 2 files 38.2 GB
BigBang-Aquila-35B-Merged-Abliterated.Q4_K_M.gguf 19.7 GB 5667a684 download
BigBang-Aquila-35B-Merged-Abliterated.Q4_K_S.gguf 18.5 GB 0efe906e download
IQ4 1 file 17.6 GB
BigBang-Aquila-35B-Merged-Abliterated.IQ4_XS.gguf 17.6 GB b1a651fa download
Q3_K 3 files 46.6 GB
BigBang-Aquila-35B-Merged-Abliterated.Q3_K_L.gguf 16.9 GB b6a2605e download
BigBang-Aquila-35B-Merged-Abliterated.Q3_K_M.gguf 15.6 GB 1438de00 download
BigBang-Aquila-35B-Merged-Abliterated.Q3_K_S.gguf 14.1 GB 7a312606 download
Q2_K 1 file 12.1 GB
BigBang-Aquila-35B-Merged-Abliterated.Q2_K.gguf 12.1 GB 9a156405 download
Auxiliary files 2 files 6.33 KB
README.md 3.93 KB bfdee6f8 download
.gitattributes 2.40 KB cc61e594 download

README current version from Hugging Face


base_model: osk-arr00/BigBang-Aquila-35B-Merged-Abliterated
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • transformers
  • safetensors
  • qwen3_5_moe
  • merge
  • abliterated
  • uncensored

About

static quants of https://huggingface.co/osk-arr00/BigBang-Aquila-35B-Merged-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/BigBang-Aquila-35B-Merged-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 13.0
GGUF Q3_K_S 15.3
GGUF Q3_K_M 16.9 lower quality
GGUF Q3_K_L 18.2
GGUF IQ4_XS 19.0
GGUF Q4_K_S 20.0 fast, recommended
GGUF Q4_K_M 21.3 fast, recommended
GGUF Q5_K_S 24.1
GGUF Q5_K_M 24.8
GGUF Q6_K 28.6 very good quality
GGUF Q8_0 37.0 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 5 versions

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

  1. 2026-09-08auto-patch README.md6862b6c3.9 KB
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  2. 2026-08-21auto-patch README.md0bf63443.9 KB
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  3. 2026-08-21auto-patch README.md1a75f063.8 KB
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  4. 2026-08-21auto-patch README.md544688c3.2 KB
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  5. 2026-08-21uploaded from marco30faea3390 B
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