Fully automatic censorship removal for language models
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Updated
Jun 27, 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.
Make abliterated models with transformers, easy and fast
Automated alignment adjustment for LLMs — direct steering, LoRA, and MoE expert-granular abliteration, optimized via multi-objective Optuna TPE.
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
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
A visual node-based pipeline studio for local AI models — uncensor, merge, compress, and deploy without writing code.
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.
Can I run this LLM? Open-source deployment intelligence for local AI — VRAM estimation, quantization selection, hardware compatibility, speed prediction. Built with FastAPI + Next.js.
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