← back to catalog · registered 2026-08-22 13:56

mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF

mradermacher Nemotron 9B GGUF second-order 1.0M ctx
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Response includes
  • classification m8
  • files 27
  • hub_downloads_all_time 12,445
  • 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 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-NVIDIA-Nemotron-Nano-9B-v2-abliterated' (base is huihui-ai model (M3))
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
12K
2K last 30d - stable
Likes
10
Model age
9mo ago
created 2026-01-05
Downloads over time
Now13.1K→from2.1K↑525%
1.5K5.8K10K14.2K2.1K on Jan 713.1K on Oct 11JanMarMayJulSep
Jan 7 → Oct 11 · 79 snapshots · spans 277 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
other
Languages
en es fr de it ja
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf nvidia pytorch abliterated uncensored en es fr de it ja

Related

Total size
124 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-01-05 07:13

Files by quantization

Q6_K 1 file 8.51 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q6_K.gguf 8.51 GB 6910cc34 download
Q5_K 2 files 12.9 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q5_K_M.gguf 6.58 GB c55c7106 download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q5_K_S.gguf 6.32 GB 5ebd9e2c download
Q4_K 2 files 11.9 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_K_M.gguf 6.08 GB c5c7470c download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_K_S.gguf 5.79 GB 678860bd download
Q4 2 files 10.4 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_1.gguf 5.43 GB 89b08684 download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_0.gguf 4.97 GB d13ae2f7 download
Q3_K 3 files 14.9 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_L.gguf 5.11 GB 05b5ce0e download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_M.gguf 5.01 GB 47caffc8 download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_S.gguf 4.78 GB eb4549b2 download
IQ4 2 files 9.85 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ4_NL.gguf 4.94 GB 149040bb download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ4_XS.gguf 4.91 GB 30d3a3a5 download
IQ3 4 files 19.1 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_M.gguf 4.85 GB aa99d74d download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_S.gguf 4.78 GB ac888a95 download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_XS.gguf 4.78 GB f634292e download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_XXS.gguf 4.73 GB 60ab211e download
Q2_K 2 files 9.37 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q2_K_S.gguf 4.71 GB ba916e99 download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q2_K.gguf 4.66 GB 5582c7e5 download
IQ2 4 files 18.4 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_M.gguf 4.65 GB 58a292e4 download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_S.gguf 4.62 GB 8fe1c89c download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_XS.gguf 4.61 GB 90d53ecb download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_XXS.gguf 4.57 GB 0c0f0086 download
IQ1 2 files 9.02 GB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ1_M.gguf 4.52 GB 08255eb1 download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ1_S.gguf 4.49 GB 45635285 download
Auxiliary files 3 files 3.75 MB
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.imatrix.gguf 3.74 MB 9ba6a53b download
README.md 7.55 KB 6e6fb740 download
.gitattributes 3.84 KB e1c5f528 download

README current version from Hugging Face


base_model: huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated
language:


About

weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated

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

static quants are available at https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-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 imatrix 0.1 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 4.9 for the desperate
GGUF i1-IQ1_M 5.0 mostly desperate
GGUF i1-IQ2_XXS 5.0
GGUF i1-IQ2_XS 5.0
GGUF i1-IQ2_S 5.1
GGUF i1-IQ2_M 5.1
GGUF i1-Q2_K 5.1 IQ3_XXS probably better
GGUF i1-Q2_K_S 5.2 very low quality
GGUF i1-IQ3_XXS 5.2 lower quality
GGUF i1-IQ3_S 5.2 beats Q3_K*
GGUF i1-IQ3_XS 5.2
GGUF i1-Q3_K_S 5.2 IQ3_XS probably better
GGUF i1-IQ3_M 5.3
GGUF i1-IQ4_XS 5.4
GGUF i1-IQ4_NL 5.4 prefer IQ4_XS
GGUF i1-Q4_0 5.4 fast, low quality
GGUF i1-Q3_K_M 5.5 IQ3_S probably better
GGUF i1-Q3_K_L 5.6 IQ3_M probably better
GGUF i1-Q4_1 5.9
GGUF i1-Q4_K_S 6.3 optimal size/speed/quality
GGUF i1-Q4_K_M 6.6 fast, recommended
GGUF i1-Q5_K_S 6.9
GGUF i1-Q5_K_M 7.2
GGUF i1-Q6_K 9.2 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. 2026-01-05auto-patch README.md438ffd17.5 KB
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  2. 2026-01-05auto-patch README.mddd3b0943.7 KB
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  3. 2026-01-05uploaded from marco0788b4d501 B
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Discussions 1 thread

  1. 2026-02-27Doesn't go in the Smart Binopen2 💬#1
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