Fully automatic censorship removal for language models
-
Updated
Jul 17, 2026 - Python
Fully automatic censorship removal for language models
Fully uncensored, capability-enhanced abliteration of Qwen3.6-27B. NVFP4 + z-lab DFlash speculative decoding (n=12) on the unified ghcr.io/aeon-7/aeon-vllm-ultimate:latest container, tuned for long-context draft acceptance on DGX Spark. 6 HF variants (BF16/NVFP4/MTP/MTP-XS), docker-compose, and QuickStart.
Automated alignment adjustment for LLMs — direct steering, LoRA, and MoE expert-granular abliteration, optimized via multi-objective Optuna TPE.
Jacobian-Brainwash : A manual alignment tool for large language models built on Anthropic's Jacobian Lens. Results are exportable.
Make abliterated models with transformers, easy and fast
Powerful no-code LLM fine-tuner: upload data → train → deploy in minutes. Unsloth 2-5× acceleration · QLoRA/DPO/RLHF/PPO/ORPO · Reward Model training · GGUF export · vLLM inference · BLEU/ROUGE/BERTScore · full CLI · Heretic Mode to unlock full model potential
Enhanced fork of Heretic (an automated LLM de-censoring tool) optimized for macOS (Apple Silicon) with checkpoint system and LM Studio integration
Gemma 4 31B Abliterated — quality-preserving guardrail removal for Google's most capable open model. Apache 2.0. Runs on Apple Silicon via MLX.
modify a language model's behavior by abliterating its weights.
Advanced abliteration framework: 8-stage pipeline, auto fine-tuning, voice support, real-time collaboration, security scanning | Production-grade LLM liberation
Layer-by-layer model training and modification for 80B+ MoE models on consumer GPUs. Abliteration, LongRoPE, LoRA merge, weight visualization. Built because nothing else could do it. https://justcalljon.pro
🚀 Train and modify 80B+ parameter Mixture of Experts models layer-by-layer on consumer GPUs using Python with AEGIS AI Trainer.
Local-first AI workstation. Run open-weight models, fine-tune, orchestrate multi-agent teams. No cloud required.
MLX-native toolkit for understanding and reshaping how language models behave on Apple Silicon
GLM-5.2, completely uncensored and fully local on 4 cards — the think-off recipe plus full serving + reproduction guide.
Toolkit to abliterate any instruct-tuned LLM using Arditi 2024 + NousResearch method
Uncensoring LLMs via Albiteration and rehabilitating via RLVR/GRPO with small post training corpus
Run Gemma 4 31B locally on Apple Silicon with full guardrail removal and no quality loss.
Lobopy is a lightweight PyTorch/HuggingFace library for analysing, steering/abliteration of causal language models.
A reproducible audit of LLM institutional-skepticism framing — 36+ models, three force-escalation rungs (prompt → pipeline → weights), five judging methods cross-validated. The bias is in the systems, not the panel scoring them.
Add a description, image, and links to the abliteration topic page so that developers can more easily learn about it.
To associate your repository with the abliteration topic, visit your repo's landing page and select "manage topics."