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mradermacher/Darkstar-Qwen3.8-27B-Abliterated-BF16-i1-GGUF

mradermacher Qwen 27B GGUF second-order 262K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
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Response includes
  • classification m8
  • files 17
  • hub_downloads_all_time 2,309
  • 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='HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-BF16' (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
2K
1K last 30d - stable
Likes
1
Model age
7w ago
created 2026-08-21
Downloads over time
Now2.5K→from259↑875%
1461K1.9K2.8K259 on Aug 192.5K on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 days

Genealogy 0 direct forks

Full fork graph →

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Variants by this author 2 formats · 2K 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
BF16
Tags
transformers gguf darkstar qwen3.8 abliterated reduced-refusal bf16 vllm en base_model:HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-BF16 base_model:quantized:HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-BF16 license:apache-2.0

Related

Total size
204 GB
Files
17
Quantizations
2
Registered
2026-08-22 13:56
Last updated on HF
2026-08-21 13:50

Files by quantization

BF16 15 files 204 GB
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q6_K.gguf 20.9 GB fa64f4e5 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q5_K_M.gguf 18.2 GB 37eef9ce download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q5_K_S.gguf 17.7 GB 42491814 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q4_1.gguf 16.2 GB 50de4064 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q4_K_M.gguf 15.7 GB a5e8bbd4 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q4_K_S.gguf 14.7 GB 3c8238ce download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q4_0.gguf 14.7 GB aac0b962 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-IQ4_XS.gguf 14.3 GB 356bca15 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q3_K_L.gguf 13.6 GB 0056b836 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q3_K_M.gguf 12.6 GB 5da368b8 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-IQ3_M.gguf 11.9 GB 6fdb2feb download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-IQ3_S.gguf 11.7 GB 534dec9c download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q3_K_S.gguf 11.4 GB 75b11ae3 download
Darkstar-Qwen3.8-27B-Abliterated-BF16.i1-Q2_K.gguf 10.1 GB 61b44ddb download
Darkstar-Qwen3.8-27B-Abliterated-BF16.imatrix.gguf 13.0 MB 06254970 download
Auxiliary files 2 files 8.12 KB
README.md 5.34 KB 31943a28 download
.gitattributes 2.78 KB 92270414 download

README current version from Hugging Face


base_model: HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-BF16
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • darkstar
  • qwen3.8
  • abliterated
  • reduced-refusal
  • bf16
  • vllm

About

weighted/imatrix quants of https://huggingface.co/HangGlidersRule/Darkstar-Qwen3.8-27B-Abliterated-BF16

For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/Darkstar-Qwen3.8-27B-Abliterated-BF16-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

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 imatrix 0.1 imatrix file (for creating your own quants)
GGUF i1-Q2_K 11.0 IQ3_XXS probably better
GGUF i1-Q3_K_S 12.4 IQ3_XS probably better
GGUF i1-IQ3_S 12.7 beats Q3_K*
GGUF i1-IQ3_M 12.9
GGUF i1-Q3_K_M 13.6 IQ3_S probably better
GGUF i1-Q3_K_L 14.7 IQ3_M probably better
GGUF i1-IQ4_XS 15.4
GGUF i1-Q4_0 15.9 fast, low quality
GGUF i1-Q4_K_S 15.9 optimal size/speed/quality
GGUF i1-Q4_K_M 16.9 fast, recommended
GGUF i1-Q4_1 17.4
GGUF i1-Q5_K_S 19.1
GGUF i1-Q5_K_M 19.6
GGUF i1-Q6_K 22.5 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 3 versions

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

  1. 2026-08-21auto-patch README.md13457c75.3 KB
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  2. 2026-08-21auto-patch README.md163c3ed3.3 KB
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  3. 2026-08-21uploaded from nico1d3f5628499 B
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