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

mradermacher/Phi4-abliterated-GGUF

mradermacher Phi GGUF second-order 16K ctx
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Response includes
  • classification m8
  • files 24
  • hub_downloads_all_time 7,846
  • 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='Undi95/Phi4-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
8K
938 last 30d - stable
Likes
4
Model age
21mo ago
created 2025-01-11
Downloads over time
Now8.1K→from300↑2,586%
02.9K5.9K8.8K300 on Jan 8, 20258.1K on Oct 11Jan '25Apr '25Jul '25Oct '25JanAprJulOct
Jan 8, 2025 → Oct 11 · 131 snapshots · spans 641 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 · 4K downloads combined

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

Metadata

Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf en base_model:Undi95/Phi4-abliterated base_model:quantized:Undi95/Phi4-abliterated endpoints_compatible region:us conversational

Related

Total size
189 GB
Files
24
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2025-05-11 21:38

Files by quantization

Q8_0 2 files 29.0 GB
phi4-abliterated.Q8_0.gguf 14.5 GB ea7c01db download
Phi4-abliterated.Q8_0.gguf 14.5 GB d0b40fb9 download
Q6_K 2 files 22.4 GB
phi4-abliterated.Q6_K.gguf 11.2 GB 855af4e1 download
Phi4-abliterated.Q6_K.gguf 11.2 GB 7fe46c47 download
Q5_K 4 files 38.7 GB
phi4-abliterated.Q5_K_M.gguf 9.88 GB dd41c0e1 download
Phi4-abliterated.Q5_K_M.gguf 9.88 GB 1885b2b6 download
phi4-abliterated.Q5_K_S.gguf 9.45 GB bdf7e319 download
Phi4-abliterated.Q5_K_S.gguf 9.45 GB 802b1e7c download
Q4_K 4 files 32.6 GB
phi4-abliterated.Q4_K_M.gguf 8.43 GB 36df2268 download
Phi4-abliterated.Q4_K_M.gguf 8.43 GB a4f795e8 download
phi4-abliterated.Q4_K_S.gguf 7.86 GB 752122f4 download
Phi4-abliterated.Q4_K_S.gguf 7.86 GB 91d5ba9f download
IQ4 2 files 14.9 GB
phi4-abliterated.IQ4_XS.gguf 7.46 GB f2288fc0 download
Phi4-abliterated.IQ4_XS.gguf 7.46 GB 68bb3c2e download
Q3_K 6 files 40.6 GB
phi4-abliterated.Q3_K_L.gguf 7.39 GB ed624bd7 download
Phi4-abliterated.Q3_K_L.gguf 7.39 GB 132f6f14 download
phi4-abliterated.Q3_K_M.gguf 6.86 GB 1a748291 download
Phi4-abliterated.Q3_K_M.gguf 6.86 GB b92a303a download
phi4-abliterated.Q3_K_S.gguf 6.06 GB 728996f7 download
Phi4-abliterated.Q3_K_S.gguf 6.06 GB d2aaa5ea download
Q2_K 2 files 10.3 GB
phi4-abliterated.Q2_K.gguf 5.17 GB 1033ce0f download
Phi4-abliterated.Q2_K.gguf 5.17 GB bdb4b34a download
Auxiliary files 2 files 7.04 KB
README.md 4.17 KB 503d85e0 download
.gitattributes 2.87 KB ebb0f812 download

README current version from Hugging Face


base_model: Undi95/Phi4-abliterated
language:

  • en
    library_name: transformers
    quantized_by: mradermacher

About

static quants of https://huggingface.co/Undi95/Phi4-abliterated

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Phi4-abliterated-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
PART 1 PART 2 Q2_K 11.2
PART 1 PART 2 Q3_K_S 13.1
PART 1 PART 2 Q3_K_M 14.8 lower quality
PART 1 PART 2 Q3_K_L 16.0
PART 1 PART 2 IQ4_XS 16.1
PART 1 PART 2 Q4_K_S 17.0 fast, recommended
PART 1 PART 2 Q4_K_M 18.2 fast, recommended
PART 1 PART 2 Q5_K_S 20.4
PART 1 PART 2 Q5_K_M 21.3
PART 1 PART 2 Q6_K 24.2 very good quality
PART 1 PART 2 Q8_0 31.3 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 7 versions

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

  1. 2025-05-11auto-patch README.mdbab00ad4.2 KB
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  2. 2025-05-10auto-patch README.md4ecf3494.2 KB
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  3. 2025-05-10auto-patch README.md0a7cae04.2 KB
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  4. 2025-05-09auto-patch README.md646d4d34.2 KB
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  5. 2025-05-08auto-patch README.md8ff301a4.1 KB
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  6. 2025-01-11auto-patch README.md44cb59f3 KB
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  7. 2025-01-11uploaded from kaos69edc5a213 B
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