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mradermacher/Mistral-Small-Instruct-2409-abliterated-i1-GGUF

mradermacher Mistral GGUF second-order 33K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FMistral-Small-Instruct-2409-abliterated-i1-GGUF"
Response includes
  • classification m8
  • files 24
  • benchmarks 5 entries
  • hub_downloads_all_time 11,000
  • 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='byroneverson/Mistral-Small-Instruct-2409-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
11K
1K last 30d - stable
Likes
1
Model age
2.0y ago
created 2024-09-24
Downloads over time
Now11.4K→from0↑0%
04.2K8.4K12.6K0 on Sep 18, 202411.4K on Oct 12Sep '24Jan '25May '25Sep '25JanMaySep
Sep 18, 2024 → Oct 12 · 150 snapshots · spans 754 days

Benchmarks

Benchmark Score Source
BBH average 0.4741211570891167 OpenLLM-v2
IFEval instruct 0.7398081534772182 OpenLLM-v2
IFEval-Prompt 0.6543438077634011 OpenLLM-v2
MATH lvl 5 0.14123867069486404 OpenLLM-v2
MMLU-Pro 0.39228723404255317 OpenLLM-v2

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
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf llm mistral chat instruct it abliterated en base_model:byroneverson/Mistral-Small-Instruct-2409-abliterated base_model:quantized:byroneverson/Mistral-Small-Instruct-2409-abliterated license:other

Related

Total size
200 GB
Files
24
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2024-09-24 17:37

Files by quantization

Q6_K 1 file 17.0 GB
Mistral-Small-Instruct-2409-abliterated.i1-Q6_K.gguf 17.0 GB 5cd4c82e download
Q5_K 2 files 28.9 GB
Mistral-Small-Instruct-2409-abliterated.i1-Q5_K_M.gguf 14.6 GB de244868 download
Mistral-Small-Instruct-2409-abliterated.i1-Q5_K_S.gguf 14.3 GB 4db95537 download
Q4_K 2 files 24.2 GB
Mistral-Small-Instruct-2409-abliterated.i1-Q4_K_M.gguf 12.4 GB 74a2ab50 download
Mistral-Small-Instruct-2409-abliterated.i1-Q4_K_S.gguf 11.8 GB f73cc336 download
Q4 1 file 11.7 GB
Mistral-Small-Instruct-2409-abliterated.i1-Q4_0.gguf 11.7 GB 476364a2 download
IQ4 1 file 11.1 GB
Mistral-Small-Instruct-2409-abliterated.i1-IQ4_XS.gguf 11.1 GB 90d25b73 download
Q3_K 3 files 29.9 GB
Mistral-Small-Instruct-2409-abliterated.i1-Q3_K_L.gguf 10.9 GB 99917ca1 download
Mistral-Small-Instruct-2409-abliterated.i1-Q3_K_M.gguf 10.0 GB 3de236f8 download
Mistral-Small-Instruct-2409-abliterated.i1-Q3_K_S.gguf 8.98 GB 2aad3fbf download
IQ3 4 files 34.9 GB
Mistral-Small-Instruct-2409-abliterated.i1-IQ3_M.gguf 9.37 GB 1131c248 download
Mistral-Small-Instruct-2409-abliterated.i1-IQ3_S.gguf 9.02 GB 9e834b55 download
Mistral-Small-Instruct-2409-abliterated.i1-IQ3_XS.gguf 8.55 GB 412af9c4 download
Mistral-Small-Instruct-2409-abliterated.i1-IQ3_XXS.gguf 8.01 GB fcdc629d download
Q2_K 1 file 7.70 GB
Mistral-Small-Instruct-2409-abliterated.i1-Q2_K.gguf 7.70 GB b13912c2 download
IQ2 4 files 25.4 GB
Mistral-Small-Instruct-2409-abliterated.i1-IQ2_M.gguf 7.10 GB 8890d1c1 download
Mistral-Small-Instruct-2409-abliterated.i1-IQ2_S.gguf 6.55 GB fde6b343 download
Mistral-Small-Instruct-2409-abliterated.i1-IQ2_XS.gguf 6.19 GB bfa0b5f1 download
Mistral-Small-Instruct-2409-abliterated.i1-IQ2_XXS.gguf 5.58 GB 43461413 download
IQ1 2 files 9.40 GB
Mistral-Small-Instruct-2409-abliterated.i1-IQ1_M.gguf 4.91 GB 04e64b14 download
Mistral-Small-Instruct-2409-abliterated.i1-IQ1_S.gguf 4.50 GB 41852d66 download
Auxiliary files 3 files 11.4 MB
imatrix.dat 11.4 MB 93f46e27 download
README.md 5.95 KB 7c178d1d download
.gitattributes 3.39 KB 3e0f773b download

README current version from Hugging Face


base_model: byroneverson/Mistral-Small-Instruct-2409-abliterated
language:


About

weighted/imatrix quants of https://huggingface.co/byroneverson/Mistral-Small-Instruct-2409-abliterated

static quants are available at https://huggingface.co/mradermacher/Mistral-Small-Instruct-2409-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 4.9 for the desperate
GGUF i1-IQ1_M 5.4 mostly desperate
GGUF i1-IQ2_XXS 6.1
GGUF i1-IQ2_XS 6.7
GGUF i1-IQ2_S 7.1
GGUF i1-IQ2_M 7.7
GGUF i1-Q2_K 8.4 IQ3_XXS probably better
GGUF i1-IQ3_XXS 8.7 lower quality
GGUF i1-IQ3_XS 9.3
GGUF i1-Q3_K_S 9.7 IQ3_XS probably better
GGUF i1-IQ3_S 9.8 beats Q3_K*
GGUF i1-IQ3_M 10.2
GGUF i1-Q3_K_M 10.9 IQ3_S probably better
GGUF i1-Q3_K_L 11.8 IQ3_M probably better
GGUF i1-IQ4_XS 12.0
GGUF i1-Q4_0 12.7 fast, low quality
GGUF i1-Q4_K_S 12.8 optimal size/speed/quality
GGUF i1-Q4_K_M 13.4 fast, recommended
GGUF i1-Q5_K_S 15.4
GGUF i1-Q5_K_M 15.8
GGUF i1-Q6_K 18.4 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. 2024-09-24auto-patch README.mde20d24f6 KB
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  2. 2024-09-24uploaded from nethype/leia9a39685260 B
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