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mradermacher/L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B-i1-GGUF

mradermacher Deepseek 13.7B GGUF MoE second-order 131K ctx
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Response includes
  • classification m8
  • files 26
  • hub_downloads_all_time 13,415
  • 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='DavidAU/L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B' (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
13K
2K last 30d - stable
Likes
2
Model age
19mo ago
created 2025-03-06
Downloads over time
Now13.8K→from1K↑1,234%
3955.3K10.2K15.1K1K on Mar 5, 202513.8K on Oct 11Mar '25Jun '25Sep '25Dec '25MarJunSep
Mar 5, 2025 → Oct 11 · 123 snapshots · spans 585 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

Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf reasoning thinking cognitivecomputations r1 llama 3.1 llama-3 llama3 llama-3.1 cot deepseek

Related

Total size
145 GB
Files
26
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2025-05-28 18:59

Files by quantization

Q6_K 1 file 10.5 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q6_K.gguf 10.5 GB 9b2f8873 download
Q5_K 2 files 17.9 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q5_K_M.gguf 9.07 GB d4d9ade2 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q5_K_S.gguf 8.83 GB 2f92a662 download
Q4 2 files 15.4 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q4_1.gguf 8.06 GB 86498518 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q4_0.gguf 7.32 GB 84b0f1bb download
Q4_K 2 files 15.1 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q4_K_M.gguf 7.76 GB 9b849417 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q4_K_S.gguf 7.35 GB b1bd468e download
IQ4 2 files 14.2 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ4_NL.gguf 7.31 GB 67e37cf2 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ4_XS.gguf 6.93 GB a191bd48 download
Q3_K 3 files 18.6 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q3_K_L.gguf 6.73 GB 01dbbe4c download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q3_K_M.gguf 6.25 GB 22c85d0f download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q3_K_S.gguf 5.67 GB 8ea77b3c download
IQ3 4 files 22.0 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ3_M.gguf 5.81 GB 7e49fc70 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ3_S.gguf 5.69 GB 4e5a3c85 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ3_XS.gguf 5.41 GB 82026635 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ3_XXS.gguf 5.06 GB 021bc9a1 download
Q2_K 2 files 9.42 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q2_K.gguf 4.86 GB c5de49da download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-Q2_K_S.gguf 4.56 GB 435261a7 download
IQ2 4 files 16.1 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ2_M.gguf 4.45 GB 16f34133 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ2_S.gguf 4.12 GB 95a36f90 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ2_XS.gguf 3.95 GB efd0a5da download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ2_XXS.gguf 3.60 GB 5d3556d5 download
IQ1 2 files 6.12 GB
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ1_M.gguf 3.19 GB 5cbb4991 download
L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B.i1-IQ1_S.gguf 2.94 GB 3764a2a7 download
Auxiliary files 2 files 12.1 KB
README.md 7.89 KB da85d033 download
.gitattributes 4.24 KB 6a839eb4 download

README current version from Hugging Face


base_model: DavidAU/L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B
language:

  • en
    library_name: transformers
    quantized_by: mradermacher
    tags:
  • reasoning
  • thinking
  • cognitivecomputations
  • r1
  • llama 3.1
  • llama-3
  • llama3
  • llama-3.1
  • cot
  • deepseek
  • Llama 3.1
  • Hermes
  • DeepHermes
  • 128k context
  • fine tune
  • merge

About

weighted/imatrix quants of https://huggingface.co/DavidAU/L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B

static quants are available at https://huggingface.co/mradermacher/L3.1-MOE-2X8B-Deepseek-DeepHermes-e32-uncensored-abliterated-13.7B-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 3.3 for the desperate
GGUF i1-IQ1_M 3.5 mostly desperate
GGUF i1-IQ2_XXS 4.0
GGUF i1-IQ2_XS 4.3
GGUF i1-IQ2_S 4.5
GGUF i1-IQ2_M 4.9
GGUF i1-Q2_K_S 5.0 very low quality
GGUF i1-Q2_K 5.3 IQ3_XXS probably better
GGUF i1-IQ3_XXS 5.5 lower quality
GGUF i1-IQ3_XS 5.9
GGUF i1-Q3_K_S 6.2 IQ3_XS probably better
GGUF i1-IQ3_S 6.2 beats Q3_K*
GGUF i1-IQ3_M 6.3
GGUF i1-Q3_K_M 6.8 IQ3_S probably better
GGUF i1-Q3_K_L 7.3 IQ3_M probably better
GGUF i1-IQ4_XS 7.5
GGUF i1-IQ4_NL 7.9 prefer IQ4_XS
GGUF i1-Q4_0 8.0 fast, low quality
GGUF i1-Q4_K_S 8.0 optimal size/speed/quality
GGUF i1-Q4_K_M 8.4 fast, recommended
GGUF i1-Q4_1 8.8
GGUF i1-Q5_K_S 9.6
GGUF i1-Q5_K_M 9.8
GGUF i1-Q6_K 11.3 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. 2025-05-28auto-patch README.mde95dfe17.9 KB
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  2. 2025-03-06auto-patch README.md50b8c947.8 KB
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  3. 2025-03-06uploaded from nico22c3f018282 B
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