← back to catalog · registered 2026-09-18 17:56

mradermacher/abliterated-minicpm5-2b-v2-GGUF

mradermacher 2B GGUF second-order
curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2Fabliterated-minicpm5-2b-v2-GGUF"
Response includes
  • classification m8
  • files 14
  • author_summary 3235 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
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='KidIkaros/abliterated-minicpm5-2b-v2' (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 · 30-day
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Model age
today
created 2026-09-18

Genealogy 0 direct forks

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Variants by this author 2 formats · 0 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 text-generation abliterated dpo llama.cpp pytorch en base_model:KidIkaros/abliterated-minicpm5-2b-v2 base_model:quantized:KidIkaros/abliterated-minicpm5-2b-v2 license:apache-2.0 endpoints_compatible

Related

Total size
21.2 GB
Files
14
Quantizations
9
Registered
2026-09-18 17:56
Last updated on HF
2026-09-18 17:28

Files by quantization

F16 1 file 4.69 GB
abliterated-minicpm5-2b-v2.f16.gguf 4.69 GB 3f822363 download
Q8_0 1 file 2.50 GB
abliterated-minicpm5-2b-v2.Q8_0.gguf 2.50 GB c2815613 download
Q6_K 1 file 1.93 GB
abliterated-minicpm5-2b-v2.Q6_K.gguf 1.93 GB 4ba18b21 download
Q5_K 2 files 3.33 GB
abliterated-minicpm5-2b-v2.Q5_K_M.gguf 1.68 GB a5bc364a download
abliterated-minicpm5-2b-v2.Q5_K_S.gguf 1.65 GB 47c519c8 download
Q4_K 2 files 2.85 GB
abliterated-minicpm5-2b-v2.Q4_K_M.gguf 1.45 GB 05dec32a download
abliterated-minicpm5-2b-v2.Q4_K_S.gguf 1.40 GB 5ff61639 download
IQ4 1 file 1.33 GB
abliterated-minicpm5-2b-v2.IQ4_XS.gguf 1.33 GB 6128df94 download
Q3_K 3 files 3.60 GB
abliterated-minicpm5-2b-v2.Q3_K_L.gguf 1.28 GB d820c02b download
abliterated-minicpm5-2b-v2.Q3_K_M.gguf 1.20 GB 87a136ad download
abliterated-minicpm5-2b-v2.Q3_K_S.gguf 1.11 GB c755a4f8 download
Q2_K 1 file 992 MB
abliterated-minicpm5-2b-v2.Q2_K.gguf 992 MB 6fe4ae19 download
Auxiliary files 2 files 6.14 KB
README.md 3.78 KB 21a10c84 download
.gitattributes 2.35 KB 81b74d40 download

README current version from Hugging Face


base_model: KidIkaros/abliterated-minicpm5-2b-v2
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • text-generation
  • abliterated
  • dpo
  • gguf
  • llama.cpp
  • pytorch

About

static quants of https://huggingface.co/KidIkaros/abliterated-minicpm5-2b-v2

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/abliterated-minicpm5-2b-v2-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 1.1
GGUF Q3_K_S 1.3
GGUF Q3_K_M 1.4 lower quality
GGUF Q3_K_L 1.5
GGUF IQ4_XS 1.5
GGUF Q4_K_S 1.6 fast, recommended
GGUF Q4_K_M 1.7 fast, recommended
GGUF Q5_K_S 1.9
GGUF Q5_K_M 1.9
GGUF Q6_K 2.2 very good quality
GGUF Q8_0 2.8 fast, best quality
GGUF f16 5.1 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.

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