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mradermacher/Mistral-Nemo-Instruct-2407-abliterated-i1-GGUF

mradermacher Mistral GGUF second-order 1.0M ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
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Response includes
  • classification m8
  • files 27
  • benchmarks 16 entries
  • hub_downloads_all_time 22,411
  • 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='natong19/Mistral-Nemo-Instruct-2407-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
22K
2K last 30d - cooling
Likes
7
Model age
2.1y ago
created 2024-09-02
Downloads over time
Now22.8K→from492↑4,544%
08.4K16.7K25.1K492 on Aug 28, 202422.8K on Oct 11Aug '24Dec '24Apr '25Aug '25Dec '25AprAug
Aug 28, 2024 → Oct 11 · 151 snapshots · spans 774 days

Benchmarks

Benchmark Score Source
BBH average 0.45868465430016864 OpenLLM-v2
IFEval instruct 0.6906474820143885 OpenLLM-v2
IFEval-Prompt 0.5878003696857671 OpenLLM-v2
MATH lvl 5 0.05664652567975831 OpenLLM-v2
MMLU-Pro 0.351811835106383 OpenLLM-v2
Entertainment 1.1 UGI
Hazardous 2.9 UGI
Natural Intelligence 23.7 UGI
Political lean -19.9% UGI
Sensitive-Info 17.93 UGI
SocPol 1.7 UGI
UGI 31.12 UGI
Willingness (10) 5.8 UGI
W10-Adherence 4.5 UGI
W10-Direct 7 UGI
Writing 38.9 UGI

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 · 3K 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 fr de es it pt ru zh ja
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf en fr de es it pt ru zh ja base_model:natong19/Mistral-Nemo-Instruct-2407-abliterated

Related

Total size
134 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2024-09-02 22:44

Files by quantization

Q6_K 1 file 9.37 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-Q6_K.gguf 9.37 GB 4468499b download
Q5_K 2 files 16.1 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-Q5_K_M.gguf 8.13 GB 9a2220ce download
Mistral-Nemo-Instruct-2407-abliterated.i1-Q5_K_S.gguf 7.93 GB 717071a2 download
Q4_K 2 files 13.6 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-Q4_K_M.gguf 6.96 GB dd23978e download
Mistral-Nemo-Instruct-2407-abliterated.i1-Q4_K_S.gguf 6.63 GB 4181f4f3 download
Q4 4 files 26.4 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-Q4_0.gguf 6.61 GB 569e9fa2 download
Mistral-Nemo-Instruct-2407-abliterated.i1-Q4_0_4_4.gguf 6.59 GB 3425fe5e download
Mistral-Nemo-Instruct-2407-abliterated.i1-Q4_0_4_8.gguf 6.59 GB 16c67e14 download
Mistral-Nemo-Instruct-2407-abliterated.i1-Q4_0_8_8.gguf 6.59 GB 34aee943 download
IQ4 1 file 6.28 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ4_XS.gguf 6.28 GB aa484f21 download
Q3_K 3 files 16.9 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-Q3_K_L.gguf 6.11 GB 61705b02 download
Mistral-Nemo-Instruct-2407-abliterated.i1-Q3_K_M.gguf 5.67 GB 704003cf download
Mistral-Nemo-Instruct-2407-abliterated.i1-Q3_K_S.gguf 5.15 GB d9bcbe1e download
IQ3 4 files 20.1 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ3_M.gguf 5.33 GB 340b4f2d download
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ3_S.gguf 5.18 GB d3e6025a download
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ3_XS.gguf 4.94 GB 9ee1dad0 download
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ3_XXS.gguf 4.61 GB 5c119b21 download
Q2_K 1 file 4.46 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-Q2_K.gguf 4.46 GB 8e90980a download
IQ2 4 files 15.0 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ2_M.gguf 4.13 GB 9254c928 download
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ2_S.gguf 3.85 GB 3b5234b2 download
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ2_XS.gguf 3.65 GB ebdc2690 download
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ2_XXS.gguf 3.35 GB bdf38faa download
IQ1 2 files 5.79 GB
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ1_M.gguf 3.00 GB c987f27e download
Mistral-Nemo-Instruct-2407-abliterated.i1-IQ1_S.gguf 2.79 GB d2b25629 download
Auxiliary files 3 files 6.74 MB
imatrix.dat 6.73 MB 02038825 download
README.md 6.44 KB 4281eaf8 download
.gitattributes 3.64 KB 4311ce85 download

README current version from Hugging Face


base_model: natong19/Mistral-Nemo-Instruct-2407-abliterated
language:

  • en
  • fr
  • de
  • es
  • it
  • pt
  • ru
  • zh
  • ja
    library_name: transformers
    license: apache-2.0
    quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/natong19/Mistral-Nemo-Instruct-2407-abliterated

static quants are available at https://huggingface.co/mradermacher/Mistral-Nemo-Instruct-2407-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 i1-IQ1_S 3.1 for the desperate
GGUF i1-IQ1_M 3.3 mostly desperate
GGUF i1-IQ2_XXS 3.7
GGUF i1-IQ2_XS 4.0
GGUF i1-IQ2_S 4.2
GGUF i1-IQ2_M 4.5
GGUF i1-Q2_K 4.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 5.0 lower quality
GGUF i1-IQ3_XS 5.4
GGUF i1-Q3_K_S 5.6 IQ3_XS probably better
GGUF i1-IQ3_S 5.7 beats Q3_K*
GGUF i1-IQ3_M 5.8
GGUF i1-Q3_K_M 6.2 IQ3_S probably better
GGUF i1-Q3_K_L 6.7 IQ3_M probably better
GGUF i1-IQ4_XS 6.8
GGUF i1-Q4_0_4_4 7.2 fast on arm, low quality
GGUF i1-Q4_0_4_8 7.2 fast on arm+i8mm, low quality
GGUF i1-Q4_0_8_8 7.2 fast on arm+sve, low quality
GGUF i1-Q4_0 7.2 fast, low quality
GGUF i1-Q4_K_S 7.2 optimal size/speed/quality
GGUF i1-Q4_K_M 7.6 fast, recommended
GGUF i1-Q5_K_S 8.6
GGUF i1-Q5_K_M 8.8
GGUF i1-Q6_K 10.2 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 2 versions

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

  1. 2024-09-02auto-patch README.mdd85201f6.4 KB
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  2. 2024-09-02uploaded from nethype/db36b51de7255 B
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