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Timamar/B.R.O-abliterated-27B

Timamar Qwen 27B GGUF
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Abliteration classifier · v1.0.0
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Primary method

Unclassified

No clear signals of an abliteration technique in this model.
Confidence
UNKNOWN
Why this label 1 signal
No classification signals present. This may not be an abliterated model at all - it could be a repackaging, a merge with unrelated goals, or unrelated content that mentions the term.
  • no classification signals present (no abliterated, uncensored, or known producer/method markers)
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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Model age
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created 2026-10-18

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Metadata

License
apache-2.0
Tags
mlx safetensors qwen3_5 cybersecurity offensive-security red-teaming abliterated uncensored gguf lora ollama text-generation

Related

Total size
0 B
Files
4
Quantizations
1
Registered
2026-10-18 21:00
Last updated on HF
2026-10-18 21:15

Files by quantization

Auxiliary files 4 files 6.23 KB
install-bro-27b-real.zsh 2.49 KB 7115b5cf download
README.md 2.21 KB 6d5f6d27 download
.gitattributes 1.48 KB a6344aac download
Modelfile 43.0 B 07e26e3e download

README current version from Hugging Face


license: apache-2.0
library_name: mlx
base_model: Qwen/Qwen3.5-27B
tags:

  • cybersecurity
  • offensive-security
  • red-teaming
  • abliterated
  • uncensored
  • mlx
  • gguf
  • lora
  • ollama
    pipeline_tag: text-generation

B.R.O — Breaching Remote Operation (B.R.O-abliterated-27B)

An uncensored 27B cyber LLM. Built on a Qwen3.5-27B base — abliterated via refusal-direction orthogonalization (Arditi et al.), then LoRA-trained (rank-16) on offensive security, red-team, reverse-engineering, binary exploitation, and deep-cyber trajectories, and fused into the base weights.

Architecture & Specifications

Property Value
Model B.R.O (Breaching Remote Operation · 27B Abliterated)
Base Qwen3.5-27B (abliterated)
Training MLX LoRA r16 (scale 20.0), fused into base weights
Quantization / Size ~20.6 GB (int4 · MLX safetensors / GGUF)
Context Window 16,384 tokens
Runtime Ollama / llama.cpp / MLX

Quick Start

Run via Ollama (Remote Host)

OLLAMA_HOST=https://bro.exody.ai ollama run bro-27b-export

Local Installation (Fused 27B INT4 / LoRA Adapters)

zsh install-bro-27b-real.zsh
ollama run BRO-27B-REAL

Or install the v17 LoRA & GGUF adapters:

zsh install-bro-27b.zsh

Included Files in This Repository

  • adapters.safetensors & adapter_config.json — MLX LoRA r16 offensive-cyber adapter weights
  • config.json, generation_config.json, model.safetensors.index.json — Model architecture & shard index
  • tokenizer.json, tokenizer_config.json, chat_template.jinja — Tokenizer & ChatML template
  • Modelfile — Ollama Modelfile configuration (num_ctx 16384)
  • install-bro-27b-real.zsh & install-bro-27b.zsh — Automated installers for the full 21 GB INT4 GGUF/safetensors release blobs
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