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

mradermacher/MFANN-Llama3.1-Abliterated-Slerp-V3.2-i1-GGUF

mradermacher Llama GGUF second-order 131K ctx
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Response includes
  • classification m8
  • files 27
  • hub_downloads_all_time 3,806
  • 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='netcat420/MFANN-Llama3.1-Abliterated-Slerp-V3.2' (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.

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Downloads · lifetime
4K
667 last 30d - stable
Likes
1
Model age
23mo ago
created 2024-10-28
Downloads over time
Now3.9K→from475↑721%
01.4K2.9K4.3K475 on Oct 23, 20243.9K on Oct 11Oct '24Feb '25Jun '25Oct '25FebJunOct
Oct 23, 2024 → Oct 11 · 142 snapshots · spans 718 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 · 946 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf mergekit merge en base_model:netcat420/MFANN-Llama3.1-Abliterated-Slerp-V3.2 base_model:quantized:netcat420/MFANN-Llama3.1-Abliterated-Slerp-V3.2 endpoints_compatible region:us imatrix conversational

Related

Total size
88.5 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2024-10-28 15:52

Files by quantization

Q6_K 1 file 6.14 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q6_K.gguf 6.14 GB 3983646b download
Q5_K 2 files 10.6 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q5_K_M.gguf 5.34 GB 3562169f download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q5_K_S.gguf 5.21 GB 94bc04e6 download
Q4_K 2 files 8.95 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q4_K_M.gguf 4.58 GB 6a6a67c5 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q4_K_S.gguf 4.37 GB 0e6a62c0 download
Q4 4 files 17.4 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q4_0.gguf 4.35 GB 121d5ad9 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q4_0_4_4.gguf 4.34 GB dffcf58f download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q4_0_4_8.gguf 4.34 GB 4bd0f326 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q4_0_8_8.gguf 4.34 GB 26830590 download
IQ4 1 file 4.14 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ4_XS.gguf 4.14 GB 686737cc download
Q3_K 3 files 11.2 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q3_K_L.gguf 4.03 GB 0eda8b78 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q3_K_M.gguf 3.74 GB 0b799210 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q3_K_S.gguf 3.41 GB c516173f download
IQ3 4 files 13.3 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ3_M.gguf 3.52 GB d032415e download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ3_S.gguf 3.43 GB 71451aea download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ3_XS.gguf 3.28 GB e8b72340 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ3_XXS.gguf 3.05 GB 3b60fa5b download
Q2_K 1 file 2.96 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-Q2_K.gguf 2.96 GB 96c7a5a1 download
IQ2 4 files 9.98 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ2_M.gguf 2.75 GB ee6a5fa7 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ2_S.gguf 2.57 GB c904f276 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ2_XS.gguf 2.43 GB 19b0bda4 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ2_XXS.gguf 2.23 GB 24ffd113 download
IQ1 2 files 3.89 GB
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ1_M.gguf 2.01 GB 6b9c1591 download
MFANN-Llama3.1-Abliterated-Slerp-V3.2.i1-IQ1_S.gguf 1.88 GB a1912b41 download
Auxiliary files 3 files 4.77 MB
imatrix.dat 4.76 MB 0fd481ef download
README.md 6.35 KB 10efdb8c download
.gitattributes 3.61 KB 0daa8b7b download

README current version from Hugging Face


base_model: netcat420/MFANN-Llama3.1-Abliterated-Slerp-V3.2
language:

  • en
    library_name: transformers
    quantized_by: mradermacher
    tags:
  • mergekit
  • merge

About

weighted/imatrix quants of https://huggingface.co/netcat420/MFANN-Llama3.1-Abliterated-Slerp-V3.2

static quants are available at https://huggingface.co/mradermacher/MFANN-Llama3.1-Abliterated-Slerp-V3.2-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 2.1 for the desperate
GGUF i1-IQ1_M 2.3 mostly desperate
GGUF i1-IQ2_XXS 2.5
GGUF i1-IQ2_XS 2.7
GGUF i1-IQ2_S 2.9
GGUF i1-IQ2_M 3.0
GGUF i1-Q2_K 3.3 IQ3_XXS probably better
GGUF i1-IQ3_XXS 3.4 lower quality
GGUF i1-IQ3_XS 3.6
GGUF i1-Q3_K_S 3.8 IQ3_XS probably better
GGUF i1-IQ3_S 3.8 beats Q3_K*
GGUF i1-IQ3_M 3.9
GGUF i1-Q3_K_M 4.1 IQ3_S probably better
GGUF i1-Q3_K_L 4.4 IQ3_M probably better
GGUF i1-IQ4_XS 4.5
GGUF i1-Q4_0_4_4 4.8 fast on arm, low quality
GGUF i1-Q4_0_4_8 4.8 fast on arm+i8mm, low quality
GGUF i1-Q4_0_8_8 4.8 fast on arm+sve, low quality
GGUF i1-Q4_0 4.8 fast, low quality
GGUF i1-Q4_K_S 4.8 optimal size/speed/quality
GGUF i1-Q4_K_M 5.0 fast, recommended
GGUF i1-Q5_K_S 5.7
GGUF i1-Q5_K_M 5.8
GGUF i1-Q6_K 6.7 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. 2024-10-28auto-patch README.mdc3f0d0f6.4 KB
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  2. 2024-10-28uploaded from nethype/db23e526f0255 B
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