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ZeroWw/gemma-3-1b-it-abliterated-GGUF

ZeroWw Gemma 1B GGUF 33K ctx
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Response includes
  • classification m8
  • files 8
  • hub_downloads_all_time 875
  • author_summary 25 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
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
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
875
78 last 30d - cooling
Likes
0
Model age
18mo ago
created 2025-03-23
Downloads over time
Now901→from136↑563%
98391684978136 on Mar 19, 2025901 on Oct 11901 on Oct 10Mar '25Jun '25Sep '25Dec '25MarJunSep
Mar 19, 2025 → Oct 11 · 121 snapshots · spans 571 days

Metadata

License
mit
Languages
en
Quantizations
F16
Tags
gguf text-generation en license:mit endpoints_compatible region:us conversational

Related

Total size
7.14 GB
Files
8
Quantizations
2
Registered
2026-08-22 13:56
Last updated on HF
2025-03-23 08:46

Files by quantization

F16 1 file 1.87 GB
gemma-3-1b-it-abliterated.f16.gguf 1.87 GB ed592320 download
Auxiliary files 7 files 5.27 GB
gemma-3-1b-it-abliterated.q8_0.gguf 1.26 GB 6876b222 download
gemma-3-1b-it-abliterated.q6_k.gguf 1.21 GB 333f85a5 download
gemma-3-1b-it-abliterated.q5_k.gguf 1.06 GB 53924012 download
gemma-3-1b-it-abliterated.q8_p.gguf 1020 MB 38e918ed download
gemma-3-1b-it-abliterated.q8q4.gguf 769 MB d57cca3c download
.gitattributes 1.90 KB 433df6b7 download
README.md 339 B 30ec09b7 download

README current version from Hugging Face


license: mit
language:

  • en
    pipeline_tag: text-generation

My own (ZeroWw) quantizations.
output and embed tensors quantized to f16.
all other tensors quantized to q5_k or q6_k.

Result:
both f16.q6 and f16.q5 are smaller than q8_0 standard quantization
and they perform as well as the pure f16.

Updated on: Sun Mar 23, 08:44:03

README history 1 version

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

  1. 2025-03-23Upload folder using huggingface_hubc4cd5ef339 B
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