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

mradermacher/Llama-3-70B-Instruct-abliterated-v3-i1-GGUF

mradermacher Llama 70B GGUF second-order 8K ctx
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Response includes
  • classification m8
  • files 26
  • hub_downloads_all_time 8,172
  • 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='Greytechai/Llama-3-70B-Instruct-abliterated-v3' (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
8K
852 last 30d - stable
Likes
0
Model age
6mo ago
created 2026-03-23
Downloads over time
Now8.5K→from7.2K↑18%
7.1K7.6K8.1K8.6K7.2K on Mar 258.5K on Oct 11MarAprMayJunJulAugSepOct
Mar 25 → Oct 11 · 68 snapshots · spans 200 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 · 1K downloads combined

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

Metadata

License
llama3
Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf en base_model:Greytechai/Llama-3-70B-Instruct-abliterated-v3 base_model:quantized:Greytechai/Llama-3-70B-Instruct-abliterated-v3 license:llama3 endpoints_compatible region:us imatrix conversational

Related

Total size
701 GB
Files
26
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-03-24 08:47

Files by quantization

Q6_K 1 file 53.9 GB
Llama-3-70B-Instruct-abliterated-v3.i1-Q6_K.gguf 53.9 GB ae3569fc download
Q5_K 2 files 91.8 GB
Llama-3-70B-Instruct-abliterated-v3.i1-Q5_K_M.gguf 46.5 GB d77c8eea download
Llama-3-70B-Instruct-abliterated-v3.i1-Q5_K_S.gguf 45.3 GB deee014e download
Q4 2 files 78.6 GB
Llama-3-70B-Instruct-abliterated-v3.i1-Q4_1.gguf 41.3 GB b6238dc4 download
Llama-3-70B-Instruct-abliterated-v3.i1-Q4_0.gguf 37.4 GB ba320d2f download
Q4_K 2 files 77.2 GB
Llama-3-70B-Instruct-abliterated-v3.i1-Q4_K_M.gguf 39.6 GB 785d0bc6 download
Llama-3-70B-Instruct-abliterated-v3.i1-Q4_K_S.gguf 37.6 GB 8b221800 download
IQ4 1 file 35.3 GB
Llama-3-70B-Instruct-abliterated-v3.i1-IQ4_XS.gguf 35.3 GB 60043c97 download
Q3_K 3 files 95.3 GB
Llama-3-70B-Instruct-abliterated-v3.i1-Q3_K_L.gguf 34.6 GB 97ca1547 download
Llama-3-70B-Instruct-abliterated-v3.i1-Q3_K_M.gguf 31.9 GB 28f8ebb3 download
Llama-3-70B-Instruct-abliterated-v3.i1-Q3_K_S.gguf 28.8 GB 1b25dd0a download
IQ3 4 files 111 GB
Llama-3-70B-Instruct-abliterated-v3.i1-IQ3_M.gguf 29.7 GB 533ca3c7 download
Llama-3-70B-Instruct-abliterated-v3.i1-IQ3_S.gguf 28.8 GB 4f0572ac download
Llama-3-70B-Instruct-abliterated-v3.i1-IQ3_XS.gguf 27.3 GB 24384179 download
Llama-3-70B-Instruct-abliterated-v3.i1-IQ3_XXS.gguf 25.6 GB 376b11c7 download
Q2_K 2 files 47.4 GB
Llama-3-70B-Instruct-abliterated-v3.i1-Q2_K.gguf 24.6 GB e55efbe1 download
Llama-3-70B-Instruct-abliterated-v3.i1-Q2_K_S.gguf 22.8 GB a8105ed7 download
IQ2 4 files 80.7 GB
Llama-3-70B-Instruct-abliterated-v3.i1-IQ2_M.gguf 22.5 GB 730a6d10 download
Llama-3-70B-Instruct-abliterated-v3.i1-IQ2_S.gguf 20.7 GB 5c89970b download
Llama-3-70B-Instruct-abliterated-v3.i1-IQ2_XS.gguf 19.7 GB 18ea1703 download
Llama-3-70B-Instruct-abliterated-v3.i1-IQ2_XXS.gguf 17.8 GB 11702018 download
IQ1 2 files 29.9 GB
Llama-3-70B-Instruct-abliterated-v3.i1-IQ1_M.gguf 15.6 GB f0d58221 download
Llama-3-70B-Instruct-abliterated-v3.i1-IQ1_S.gguf 14.3 GB e7d3aa60 download
Auxiliary files 3 files 23.8 MB
Llama-3-70B-Instruct-abliterated-v3.imatrix.gguf 23.8 MB 28a50961 download
README.md 6.65 KB 2ac77c88 download
.gitattributes 3.51 KB 4ada5e9e download

README current version from Hugging Face


base_model: Greytechai/Llama-3-70B-Instruct-abliterated-v3
language:

  • en
    library_name: transformers
    license: llama3
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/Greytechai/Llama-3-70B-Instruct-abliterated-v3

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

static quants are available at https://huggingface.co/mradermacher/Llama-3-70B-Instruct-abliterated-v3-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 15.4 for the desperate
GGUF i1-IQ1_M 16.9 mostly desperate
GGUF i1-IQ2_XXS 19.2
GGUF i1-IQ2_XS 21.2
GGUF i1-IQ2_S 22.3
GGUF i1-IQ2_M 24.2
GGUF i1-Q2_K_S 24.6 very low quality
GGUF i1-Q2_K 26.5 IQ3_XXS probably better
GGUF i1-IQ3_XXS 27.6 lower quality
GGUF i1-IQ3_XS 29.4
GGUF i1-IQ3_S 31.0 beats Q3_K*
GGUF i1-Q3_K_S 31.0 IQ3_XS probably better
GGUF i1-IQ3_M 32.0
GGUF i1-Q3_K_M 34.4 IQ3_S probably better
GGUF i1-Q3_K_L 37.2 IQ3_M probably better
GGUF i1-IQ4_XS 38.0
GGUF i1-Q4_0 40.2 fast, low quality
GGUF i1-Q4_K_S 40.4 optimal size/speed/quality
GGUF i1-Q4_K_M 42.6 fast, recommended
GGUF i1-Q4_1 44.4
GGUF i1-Q5_K_S 48.8
GGUF i1-Q5_K_M 50.0
GGUF i1-Q6_K 58.0 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 11 versions

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

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  11. 2026-03-23uploaded from rich13907077492 B
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