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usermma/Holo-3.1-9B-abliterated-rdo

usermma 9.0B
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/usermma%2FHolo-3.1-9B-abliterated-rdo"
Response includes
  • classification m1
  • files 21
  • hub_downloads_all_time 69
  • author_summary 77 models
  • readme_text full
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 GET/methods/m1
What "m1" means · taxonomy
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
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=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
How we label → About M1 →
Refusal direction extracted via
Extraction technique

Difference-of-means

FromArditi et al. (2024) ↗
Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
What is a refusal direction? → Read the paper ↗
Downloads · lifetime
69
14 last 30d - stable
Likes
1
Descendants
2
in 2 direct forks
Model age
4mo ago
created 2026-06-05
Downloads over time
Now75→from25↑200%
2342618025 on Jun 1075 on Oct 1175 on Oct 8JunJulAugSepOct
Jun 10 → Oct 11 · 57 snapshots · spans 123 days

Genealogy 2 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.

Hcompany/Holo-3.1-9B this lineage
usermma/Holo-3.1-9B-abliterated-rdo↓ 14 2 forks
mradermacher/Holo-3.1-9B-abliterated-rdo-i1-GGUF↓ 1,359
mradermacher/Holo-3.1-9B-abliterated-rdo-GGUF↓ 532

Metadata

Tags
safetensors qwen3_5_text obliteratus abliteration uncensored obliterate en base_model:Hcompany/Holo-3.1-9B base_model:finetune:Hcompany/Holo-3.1-9B region:us

Related

Other by usermma
Huihui-MiniCPM5-1B-abliterated-mlx-2Bit 279 Huihui-LFM2.5-8B-A1B-abliterated-mlx-2Bit 166 Huihui-LFM2.5-8B-A1B-abliterated-mlx-fp16 164 Qwythos-9B-v2-Heretic-Abliterated 133 DeepHat-V1-7B-Heretic-Abliterated-mlx-8Bit 126
Total size
16.7 GB
Files
21
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-06-05 09:18
Source huggingface.co/usermma/Holo-3.1-9B-abliterated-rdo ↗ Base model Hcompany/Holo-3.1-9B ↗

Files by quantization

Auxiliary files 21 files 16.7 GB
model-00001-of-00010.safetensors 1.89 GB b75dd125 download
model-00009-of-00010.safetensors 1.89 GB d141852d download
model-00007-of-00010.safetensors 1.86 GB 7f254414 download
model-00008-of-00010.safetensors 1.85 GB 290a6962 download
model-00002-of-00010.safetensors 1.83 GB 34ec18bf download
model-00005-of-00010.safetensors 1.83 GB 99102558 download
model-00003-of-00010.safetensors 1.83 GB 7ec635db download
model-00006-of-00010.safetensors 1.80 GB 4deb4bfa download
model-00004-of-00010.safetensors 1.80 GB 96672047 download
model-00010-of-00010.safetensors 96.0 MB 87308640 download
tokenizer.json 19.1 MB 0f069a09 download
model.safetensors.index.json 34.8 KB 5edc660f download
chat_template.jinja 7.57 KB a585dec8 download
config.json 1.90 KB 9f0555af download
abliteration_metadata.json 1.60 KB 6c26411b download
.gitattributes 1.53 KB 52373fe2 download
tokenizer_config.json 1.26 KB 5db46b93 download
README.md 1.05 KB a266766d download
obliteratus_session.json 219 B 7e1dd35c download
generation_config.json 135 B 0ed7952c download
.quick_checkpoint 18.0 B 27769b5b download

README current version from Hugging Face

language: en
tags:

  • obliteratus
  • abliteration
  • uncensored
  • obliterate
    base_model: Hcompany/Holo-3.1-9B

Holo-3.1-9B-OBLITERATED

This model was abliterated using the rdo method via
OBLITERATUS.

Detail Value
Base model Hcompany/Holo-3.1-9B
Method rdo
Source obliterate

How to Use

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Holo-3.1-9B-OBLITERATED")
tokenizer = AutoTokenizer.from_pretrained("Holo-3.1-9B-OBLITERATED")

prompt = "Hello, how are you?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

About OBLITERATUS

OBLITERATUS is an open-source tool for removing refusal behavior from language
models via activation engineering (abliteration). Learn more at
github.com/elder-plinius/OBLITERATUS.

README history 1 version

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

  1. 2026-06-05OBLITERATUS: rdo on Hcompany/Holo-3.1-9B493f31b1 KB
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