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mradermacher/tinyllama-1.1b-abliterated-GGUF

mradermacher 1.1B GGUF second-order 2K ctx
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     "https://abliteration.org/api/v1/models/mradermacher%2Ftinyllama-1.1b-abliterated-GGUF"
Response includes
  • classification m8
  • files 14
  • hub_downloads_all_time 872
  • 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='ops-malware/tinyllama-1.1b-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
872
447 last 30d - active
Likes
0
Model age
2mo ago
created 2026-07-28
Downloads over time
Now1.1K→from291↑276%
2515598671.2K291 on Jul 291.1K on Oct 11JulAugSepOct
Jul 29 → Oct 11 · 51 snapshots · spans 74 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

License
apache-2.0
Languages
en
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored refusal-removal interpretability senbonzakura en base_model:ElementMerc/tinyllama-1.1b-abliterated base_model:quantized:ElementMerc/tinyllama-1.1b-abliterated license:apache-2.0 endpoints_compatible

Related

Total size
9.14 GB
Files
14
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-10-06 03:24

Files by quantization

F16 1 file 2.05 GB
tinyllama-1.1b-abliterated.f16.gguf 2.05 GB 787f8438 download
Q8_0 1 file 1.09 GB
tinyllama-1.1b-abliterated.Q8_0.gguf 1.09 GB 6bf3028c download
Q6_K 1 file 862 MB
tinyllama-1.1b-abliterated.Q6_K.gguf 862 MB 3ce75b68 download
Q5_K 2 files 1.44 GB
tinyllama-1.1b-abliterated.Q5_K_M.gguf 746 MB 9dfc449a download
tinyllama-1.1b-abliterated.Q5_K_S.gguf 731 MB 7395f9b4 download
Q4_K 2 files 1.22 GB
tinyllama-1.1b-abliterated.Q4_K_M.gguf 637 MB 10cd52b8 download
tinyllama-1.1b-abliterated.Q4_K_S.gguf 610 MB 03573255 download
IQ4 1 file 582 MB
tinyllama-1.1b-abliterated.IQ4_XS.gguf 582 MB 2b103f9f download
Q3_K 3 files 1.53 GB
tinyllama-1.1b-abliterated.Q3_K_L.gguf 564 MB df45cd8f download
tinyllama-1.1b-abliterated.Q3_K_M.gguf 523 MB 6abe33f8 download
tinyllama-1.1b-abliterated.Q3_K_S.gguf 476 MB c84a7372 download
Q2_K 1 file 412 MB
tinyllama-1.1b-abliterated.Q2_K.gguf 412 MB 19386409 download
Auxiliary files 2 files 6.15 KB
README.md 3.80 KB 80b9e471 download
.gitattributes 2.35 KB 53950a03 download

README current version from Hugging Face


base_model: ops-malware/tinyllama-1.1b-abliterated
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored
  • refusal-removal
  • interpretability
  • senbonzakura

About

static quants of https://huggingface.co/ops-malware/tinyllama-1.1b-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/tinyllama-1.1b-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 0.5
GGUF Q3_K_S 0.6
GGUF Q3_K_M 0.6 lower quality
GGUF Q3_K_L 0.7
GGUF IQ4_XS 0.7
GGUF Q4_K_S 0.7 fast, recommended
GGUF Q4_K_M 0.8 fast, recommended
GGUF Q5_K_S 0.9
GGUF Q5_K_M 0.9
GGUF Q6_K 1.0 very good quality
GGUF Q8_0 1.3 fast, best quality
GGUF f16 2.3 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 4 versions

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

  1. 2026-10-06auto-patch README.md9c156ba3.8 KB
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  2. 2026-07-28auto-patch README.mdd5f5cfa3.8 KB
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  3. 2026-07-28auto-patch README.mdf749a703.9 KB
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  4. 2026-07-28uploaded from back7413ddf381 B
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