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usermma/DeepHat-V1-7B-Heretic-Abliterated

usermma Qwen 7.6B
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Response includes
  • classification m3
  • files 20
  • hub_downloads_all_time 84
  • author_summary 77 models
  • readme_text full
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Abliteration classifier · v1.0.0
M3
Primary method

Layer-wise ablation

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 2 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • 'heretic' in model name (Heretic-produced)
  • Heretic uses layer-wise optimization (M3) with underlying direction removal (M1)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
HIGH
Why we say so
name contains 'heretic'; Heretic default extraction is difference-of-means (Arditi 2024)
Downloads · lifetime
84
53 last 30d - active
Likes
2
Descendants
9
in 9 direct forks
Model age
3mo ago
created 2026-07-10
Downloads over time
Now105→from29↑262%
25548311329 on Jul 15105 on Oct 11105 on Oct 9JulAugSepOct
Jul 15 → Oct 11 · 53 snapshots · spans 88 days

Genealogy 9 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 · 92 downloads combined

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

Metadata

Tags
safetensors qwen2 obliteratus abliteration uncensored obliterate en base_model:DeepHat/DeepHat-V1-7B base_model:finetune:DeepHat/DeepHat-V1-7B region:us

Related

Total size
14.2 GB
Files
20
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-07-10 08:42

Files by quantization

Auxiliary files 20 files 14.2 GB
model-00001-of-00009.safetensors 1.76 GB 2cbfb6d7 download
model-00005-of-00009.safetensors 1.74 GB 6c397b32 download
model-00006-of-00009.safetensors 1.74 GB ce5352fc download
model-00007-of-00009.safetensors 1.74 GB 786ed9ce download
model-00004-of-00009.safetensors 1.74 GB c612f789 download
model-00002-of-00009.safetensors 1.74 GB 1d355c09 download
model-00003-of-00009.safetensors 1.74 GB 072cc035 download
model-00009-of-00009.safetensors 1.02 GB 95ca0db8 download
model-00008-of-00009.safetensors 1019 MB ed1a6f5c download
tokenizer.json 10.9 MB 15d73866 download
model.safetensors.index.json 27.1 KB 7d2384a0 download
chat_template.jinja 3.46 KB 108c998c download
abliteration_metadata.json 1.63 KB 0340cc36 download
.gitattributes 1.53 KB 52373fe2 download
config.json 1.34 KB ea3144d8 download
README.md 1.06 KB ce5a4786 download
tokenizer_config.json 483 B ce8c735d download
obliteratus_session.json 241 B c3f81930 download
generation_config.json 158 B f3555397 download
.quick_checkpoint 18.0 B 27769b5b download

README current version from Hugging Face


language: en
tags:

  • obliteratus
  • abliteration
  • uncensored
  • obliterate
    base_model: DeepHat/DeepHat-V1-7B

DeepHat-V1-7B-OBLITERATED

This model was abliterated using the heretic method via
OBLITERATUS.

Detail Value
Base model DeepHat/DeepHat-V1-7B
Method heretic
Source obliterate

How to Use

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("DeepHat-V1-7B-OBLITERATED")
tokenizer = AutoTokenizer.from_pretrained("DeepHat-V1-7B-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. 2026-07-10OBLITERATUS: heretic on DeepHat/DeepHat-V1-7B9c9ec621.1 KB
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