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mradermacher/aya-expanse-8b-abliterated-GGUF

mradermacher 8B GGUF second-order 8K ctx
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     "https://abliteration.org/api/v1/models/mradermacher%2Faya-expanse-8b-abliterated-GGUF"
Response includes
  • classification m8
  • files 15
  • hub_downloads_all_time 16,439
  • author_summary 3327 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='lenML/aya-expanse-8b-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.

What is a refusal direction? →
Downloads · lifetime
16K
609 last 30d - cooling
Likes
6
Model age
23mo ago
created 2024-11-13
Downloads over time
Now16.6K→from442↑3,647%
06.1K12.1K18.2K442 on Nov 13, 202416.6K on Oct 12Nov '24Feb '25May '25Aug '25Nov '25FebMayAug
Nov 13, 2024 → Oct 12 · 140 snapshots · spans 698 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 · 2K downloads combined

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

Metadata

Languages
en fr de es it pt ja ko zh ar el fa pl id cs he hi nl ro ru tr uk vi
Quantizations
F16 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf CohereForAI en fr de es it pt ja ko zh

Related

Total size
72.7 GB
Files
15
Quantizations
10
Registered
2026-08-22 13:56
Last updated on HF
2024-11-14 03:00

Files by quantization

F16 1 file 15.0 GB
aya-expanse-8b-abliterated.f16.gguf 15.0 GB bdeda352 download
Q8_0 1 file 7.95 GB
aya-expanse-8b-abliterated.Q8_0.gguf 7.95 GB 35d1e6ac download
Q6_K 1 file 6.14 GB
aya-expanse-8b-abliterated.Q6_K.gguf 6.14 GB 9275e541 download
Q5_K 2 files 10.7 GB
aya-expanse-8b-abliterated.Q5_K_M.gguf 5.40 GB 298fc1f8 download
aya-expanse-8b-abliterated.Q5_K_S.gguf 5.28 GB fc698c76 download
Q4_K 2 files 9.21 GB
aya-expanse-8b-abliterated.Q4_K_M.gguf 4.71 GB 0cf2d240 download
aya-expanse-8b-abliterated.Q4_K_S.gguf 4.50 GB a46fc2db download
Q4 1 file 4.47 GB
aya-expanse-8b-abliterated.Q4_0_4_4.gguf 4.47 GB c775f51a download
IQ4 1 file 4.32 GB
aya-expanse-8b-abliterated.IQ4_XS.gguf 4.32 GB f57b9fbb download
Q3_K 3 files 11.8 GB
aya-expanse-8b-abliterated.Q3_K_L.gguf 4.22 GB c5495b55 download
aya-expanse-8b-abliterated.Q3_K_M.gguf 3.93 GB c6e9d788 download
aya-expanse-8b-abliterated.Q3_K_S.gguf 3.60 GB d8abf585 download
Q2_K 1 file 3.20 GB
aya-expanse-8b-abliterated.Q2_K.gguf 3.20 GB 45650786 download
Auxiliary files 2 files 6.12 KB
README.md 3.69 KB 5caf766c download
.gitattributes 2.43 KB c6ec54ff download

README current version from Hugging Face


base_model: lenML/aya-expanse-8b-abliterated
language:

  • en
  • fr
  • de
  • es
  • it
  • pt
  • ja
  • ko
  • zh
  • ar
  • el
  • fa
  • pl
  • id
  • cs
  • he
  • hi
  • nl
  • ro
  • ru
  • tr
  • uk
  • vi
    library_name: transformers
    license: cc-by-nc-4.0
    quantized_by: mradermacher
    tags:
  • gguf
  • CohereForAI

About

static quants of https://huggingface.co/lenML/aya-expanse-8b-abliterated

weighted/imatrix quants are available at https://huggingface.co/mradermacher/aya-expanse-8b-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 3.5
GGUF Q3_K_S 4.0
GGUF Q3_K_M 4.3 lower quality
GGUF Q3_K_L 4.6
GGUF IQ4_XS 4.7
GGUF Q4_0_4_4 4.9 fast on arm, low quality
GGUF Q4_K_S 4.9 fast, recommended
GGUF Q4_K_M 5.2 fast, recommended
GGUF Q5_K_S 5.8
GGUF Q5_K_M 5.9
GGUF Q6_K 6.7 very good quality
GGUF Q8_0 8.6 fast, best quality
GGUF f16 16.2 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. 2024-11-14auto-patch README.mdcd24f8f3.7 KB
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  2. 2024-11-14auto-patch README.md12f01163.8 KB
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  3. 2024-11-13uploaded from nethype/db30df01e1222 B
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