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

NOIRAgentic/qwopus-omnicoder-abliterated

NOIRAgentic Qwen 9.7B
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model. 

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/NOIRAgentic%2Fqwopus-omnicoder-abliterated"
Response includes
  • classification m1
  • files 18
  • benchmarks 11 entries
  • hub_downloads_all_time 270
  • author_summary 1 models
  • readme_text full
Try next
GET/models?family=qwen&method=m1
Sibling qwen models · same method
 GET/methods/m1
What "m1" means · taxonomy
10 credits · hourly refresh · ~4 KB payload Get an API key →
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
270
16 last 30d - cooling
Likes
1
Descendants
2
in 2 direct forks
Model age
6mo ago
created 2026-04-05
Downloads over time
Now276→from228↑21%
226244262281228 on Apr 15276 on Oct 12AprMayJunJulAugSepOct
Apr 15 → Oct 12 · 66 snapshots · spans 180 days

Benchmarks

Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
Entertainment 1.4 UGI
Hazardous 2.4 UGI
Natural Intelligence 17.62 UGI
Political lean -12.2% UGI
Sensitive-Info 14.65 UGI
SocPol 0.9 UGI
UGI 17.27 UGI
Willingness (10) 2.2 UGI
W10-Adherence 1.5 UGI
W10-Direct 3 UGI
Writing 33.52 UGI

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.

Qwen/Qwen3.5-9B this lineage
NOIRAgentic/qwopus-omnicoder-abliterated↓ 16 2 forks
mradermacher/qwopus-omnicoder-abliterated-i1-GGUF↓ 1,071
mradermacher/qwopus-omnicoder-abliterated-GGUF↓ 381

Metadata

License
other
Tags
safetensors qwen3_5 arxiv:1910.09700 base_model:Jackrong/Qwopus3.5-9B-v3 base_model:finetune:Jackrong/Qwopus3.5-9B-v3 license:other region:us

Related

Same base model
HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive 713K lukey03/Qwen3.5-9B-abliterated-GGUF 49K prithivMLmods/Gliese-Qwen3.5-9B-Abliterated-Caption 11K Ngixdev/OmniCoder-Qwen3.5-9B-Claude-4.6-Opus-Uncensored-v2-GGUF 7K huihui-ai/Huihui-Qwen3.5-9B-abliterated 7K
Total size
18.0 GB
Files
18
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-04-05 10:54
Source huggingface.co/NOIRAgentic/qwopus-omnicoder-abliterated ↗ Base model Qwen/Qwen3.5-9B ↗

Files by quantization

Auxiliary files 18 files 18.0 GB
model-00004.safetensors 2.97 GB f037bcb8 download
model-00005.safetensors 2.97 GB 7ab56f92 download
model-00002.safetensors 2.93 GB c106ad3e download
model-00003.safetensors 2.91 GB 5eeb32ac download
model-00006.safetensors 2.91 GB 614b307a download
model-00001.safetensors 1.89 GB 106ec926 download
model-00007.safetensors 1.40 GB f1a833e6 download
tokenizer.json 12.2 MB 5f9e4d49 download
vocab.json 6.41 MB 0aa0ce06 download
model.safetensors.index.json 61.9 KB b932804e download
tokenizer_config.json 16.3 KB eda48d3e download
chat_template.jinja 7.57 KB a585dec8 download
README.md 5.25 KB 3ee1dc06 download
config.json 3.05 KB 273ce437 download
.gitattributes 1.53 KB 52373fe2 download
preprocessor_config.json 391 B e8de78a2 download
video_preprocessor_config.json 386 B a8b93603 download
LICENSE 0 B e69de29b download

README current version from Hugging Face

license: other
license_name: noiragentic
license_link: LICENSE
base_model:

  • Qwen/Qwen3.5-9B
  • Jackrong/Qwopus3.5-9B-v3
  • Tesslate/OmniCoder-9B

Model Card for Model ID

This modelcard aims to be a base template for new models. It has been generated using this raw template.

Model Details

Model Description

  • Developed by: [More Information Needed]
  • Funded by [optional]: [More Information Needed]
  • Shared by [optional]: [More Information Needed]
  • Model type: [More Information Needed]
  • Language(s) (NLP): [More Information Needed]
  • License: [More Information Needed]
  • Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

  • Repository: [More Information Needed]
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

Direct Use

[More Information Needed]

Downstream Use [optional]

[More Information Needed]

Out-of-Scope Use

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

Training Details

Training Data

[More Information Needed]

Training Procedure

Preprocessing [optional]

[More Information Needed]

Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

[More Information Needed]

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Summary

Model Examination [optional]

[More Information Needed]

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: [More Information Needed]
  • Hours used: [More Information Needed]
  • Cloud Provider: [More Information Needed]
  • Compute Region: [More Information Needed]
  • Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

[More Information Needed]

Compute Infrastructure

[More Information Needed]

Hardware

[More Information Needed]

Software

[More Information Needed]

Citation [optional]

BibTeX:

[More Information Needed]

APA:

[More Information Needed]

Glossary [optional]

[More Information Needed]

More Information [optional]

[More Information Needed]

Model Card Authors [optional]

[More Information Needed]

Model Card Contact

[More Information Needed]

README history 2 versions

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

  1. 2026-04-05Update README.md69430f25.2 KB
    Loading...
  2. 2026-04-05initial commitd320c0b71 B
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Get the app Browse the catalog
Open in Abliteration