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mradermacher/Codestral-22B-v0.1-abliterated-v3-GGUF

mradermacher 22B GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 16
  • hub_downloads_all_time 7,727
  • 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='failspy/Codestral-22B-v0.1-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.

What is a refusal direction? →
Downloads · lifetime
8K
976 last 30d - stable
Likes
1
Model age
2.4y ago
created 2024-06-04
Downloads over time
Now8.1K→from109↑7,287%
03K5.9K8.9K109 on Jul 24, 20248.1K on Oct 11Jul '24Nov '24Mar '25Jul '25Nov '25MarJul
Jul 24, 2024 → Oct 11 · 157 snapshots · spans 809 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 · 3K downloads combined

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

Metadata

Languages
en
Quantizations
IQ3 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf en base_model:failspy/Codestral-22B-v0.1-abliterated-v3 base_model:quantized:failspy/Codestral-22B-v0.1-abliterated-v3 endpoints_compatible region:us

Related

Total size
168 GB
Files
16
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2024-06-04 10:25

Files by quantization

Q8_0 1 file 22.0 GB
Codestral-22B-v0.1-abliterated-v3.Q8_0.gguf 22.0 GB bb79aed8 download
Q6_K 1 file 17.0 GB
Codestral-22B-v0.1-abliterated-v3.Q6_K.gguf 17.0 GB efde3958 download
Q5_K 2 files 28.9 GB
Codestral-22B-v0.1-abliterated-v3.Q5_K_M.gguf 14.6 GB c7f7a682 download
Codestral-22B-v0.1-abliterated-v3.Q5_K_S.gguf 14.3 GB b6f86d3b download
Q4_K 2 files 24.2 GB
Codestral-22B-v0.1-abliterated-v3.Q4_K_M.gguf 12.4 GB 25d74568 download
Codestral-22B-v0.1-abliterated-v3.Q4_K_S.gguf 11.8 GB ef6d3975 download
IQ4 1 file 11.2 GB
Codestral-22B-v0.1-abliterated-v3.IQ4_XS.gguf 11.2 GB a5c7e220 download
Q3_K 3 files 29.9 GB
Codestral-22B-v0.1-abliterated-v3.Q3_K_L.gguf 10.9 GB 82499ee0 download
Codestral-22B-v0.1-abliterated-v3.Q3_K_M.gguf 10.0 GB 94da3ef7 download
Codestral-22B-v0.1-abliterated-v3.Q3_K_S.gguf 8.98 GB eb29db83 download
IQ3 3 files 26.9 GB
Codestral-22B-v0.1-abliterated-v3.IQ3_M.gguf 9.37 GB 59bdde8f download
Codestral-22B-v0.1-abliterated-v3.IQ3_S.gguf 9.02 GB 95b1e0ae download
Codestral-22B-v0.1-abliterated-v3.IQ3_XS.gguf 8.55 GB c58a9b4c download
Q2_K 1 file 7.70 GB
Codestral-22B-v0.1-abliterated-v3.Q2_K.gguf 7.70 GB 8df08606 download
Auxiliary files 2 files 6.47 KB
README.md 3.88 KB 42a12b56 download
.gitattributes 2.60 KB bd61b678 download

README current version from Hugging Face


base_model: failspy/Codestral-22B-v0.1-abliterated-v3
language:

  • en
    library_name: transformers
    quantized_by: mradermacher

About

static quants of https://huggingface.co/failspy/Codestral-22B-v0.1-abliterated-v3

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Codestral-22B-v0.1-abliterated-v3-i1-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 Q2_K 8.4
GGUF IQ3_XS 9.3
GGUF Q3_K_S 9.7
GGUF IQ3_S 9.8 beats Q3_K*
GGUF IQ3_M 10.2
GGUF Q3_K_M 10.9 lower quality
GGUF Q3_K_L 11.8
GGUF IQ4_XS 12.1
GGUF Q4_K_S 12.8 fast, recommended
GGUF Q4_K_M 13.4 fast, recommended
GGUF Q5_K_S 15.4
GGUF Q5_K_M 15.8
GGUF Q6_K 18.4 very good quality
GGUF Q8_0 23.7 fast, best quality

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.

README history 5 versions

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

  1. 2024-06-04auto-patch README.mdd6a4b0d3.9 KB
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  2. 2024-06-04auto-patch README.mdcdd6c1f4 KB
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  3. 2024-06-04auto-patch README.md24dcfbb2.5 KB
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  4. 2024-06-04auto-patch README.md902b7661.8 KB
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  5. 2024-06-04uploaded from nethype/db210d924b231 B
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