← back to catalog · registered 2026-09-14 13:56

mradermacher/Huihui-MiniCPM5-2B-abliterated-GGUF

mradermacher 2B GGUF second-order
Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of layer-wise ablation 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='huihui-ai/Huihui-MiniCPM5-2B-abliterated' (base is huihui-ai model (M3))
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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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Model age
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created 2026-09-14

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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 zh
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf minicpm minicpm5 llama text-generation long-context tool-calling on-device edge-ai abliterated uncensored

Related

Total size
21.2 GB
Files
14
Quantizations
9
Registered
2026-09-14 13:56
Last updated on HF
2026-09-14 15:27

Files by quantization

F16 1 file 4.69 GB
Huihui-MiniCPM5-2B-abliterated.f16.gguf 4.69 GB b4b64329 download
Q8_0 1 file 2.50 GB
Huihui-MiniCPM5-2B-abliterated.Q8_0.gguf 2.50 GB ffc8f95b download
Q6_K 1 file 1.93 GB
Huihui-MiniCPM5-2B-abliterated.Q6_K.gguf 1.93 GB 0d820ffe download
Q5_K 2 files 3.33 GB
Huihui-MiniCPM5-2B-abliterated.Q5_K_M.gguf 1.68 GB b20082d4 download
Huihui-MiniCPM5-2B-abliterated.Q5_K_S.gguf 1.65 GB 2c1450bb download
Q4_K 2 files 2.85 GB
Huihui-MiniCPM5-2B-abliterated.Q4_K_M.gguf 1.45 GB fdda29a9 download
Huihui-MiniCPM5-2B-abliterated.Q4_K_S.gguf 1.40 GB 62ed1263 download
IQ4 1 file 1.33 GB
Huihui-MiniCPM5-2B-abliterated.IQ4_XS.gguf 1.33 GB ca4e8731 download
Q3_K 3 files 3.60 GB
Huihui-MiniCPM5-2B-abliterated.Q3_K_L.gguf 1.28 GB 034e7332 download
Huihui-MiniCPM5-2B-abliterated.Q3_K_M.gguf 1.20 GB f575f807 download
Huihui-MiniCPM5-2B-abliterated.Q3_K_S.gguf 1.11 GB 6b36915e download
Q2_K 1 file 992 MB
Huihui-MiniCPM5-2B-abliterated.Q2_K.gguf 992 MB 4f08acc4 download
Auxiliary files 2 files 6.47 KB
README.md 4.07 KB 42b68219 download
.gitattributes 2.40 KB c32596c6 download

README current version from Hugging Face


base_model: huihui-ai/Huihui-MiniCPM5-2B-abliterated
language:

  • en
  • zh
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • minicpm
  • minicpm5
  • llama
  • text-generation
  • long-context
  • tool-calling
  • on-device
  • edge-ai
  • abliterated
  • uncensored
  • huihui

About

static quants of https://huggingface.co/huihui-ai/Huihui-MiniCPM5-2B-abliterated

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

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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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