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是一款全自动的 LLM 审查去除工具，基于方向性消融技术（abliteration）和 Optuna 优化器，无需人工调参即可为 transformer 语言模型移除安全对齐，保留模型原有能力。","\u003Ch2 id=\"项目概述\">项目概述\u003C\u002Fh2>\u003Cp>Heretic 是一款全自动的 LLM 审查去除工具，基于方向性消融技术（Abliteration）结合 Optuna TPE 优化器，无需人工调参即可为 transformer 语言模型移除安全对齐（censorship），在保留模型智力水平的同时大幅减少拒绝回答。\u003C\u002Fp>\n\u003Ch2 id=\"主要功能\">主要功能\u003C\u002Fh2>\u003Cul>\n\u003Cli>全自动运行：无需配置，一条命令完成去审查\u003C\u002Fli>\n\u003Cli>Abliteration 技术：结合 LLM 内部语义进行定向消融\u003C\u002Fli>\n\u003Cli>KL 散度优化：最小化对原模型智能的损害\u003C\u002Fli>\n\u003Cli>广泛模型支持：密集模型、多模态模型、MoE 架构\u003C\u002Fli>\n\u003Cli>量化支持：bitsandbytes 4-bit 量化降低显存需求\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"适用人群\">适用人群\u003C\u002Fh2>\u003Cul>\n\u003Cli>本地部署 LLM 的研究者和爱好者\u003C\u002Fli>\n\u003Cli>希望获得无审查回复的 AI 用户\u003C\u002Fli>\n\u003Cli>对模型解释学研究感兴趣的技术人员\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"快速上手\">快速上手\u003C\u002Fh2>\u003Col>\n\u003Cli>安装 Python 3.10+ 环境，确保 PyTorch 2.2+ 已安装\u003C\u002Fli>\n\u003Cli>安装 Heretic：\u003Ccode>pip install -U heretic-llm\u003C\u002Fcode>\u003C\u002Fli>\n\u003Cli>运行去审查：\u003Ccode>heretic Qwen\u002FQwen3-4B-Instruct-2507\u003C\u002Fcode>\u003C\u002Fli>\n\u003Cli>完成后可选择保存模型、上传 HuggingFace、测试对话或运行基准测试\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Ch2 id=\"核心优势\">核心优势\u003C\u002Fh2>\u003Cul>\n\u003Cli>完全自动化，无需理解 transformer 内部原理\u003C\u002Fli>\n\u003Cli>在拒绝抑制和 KL 散度上均优于手动消融版本\u003C\u002Fli>\n\u003Cli>支持模型量化，16GB VRAM 即可运行 4B 模型\u003C\u002Fli>\n\u003Cli>社区已生成超过 5000 个 Heretic 模型\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"系统要求\">系统要求\u003C\u002Fh2>\u003Cul>\n\u003Cli>操作系统：Linux（推荐）、macOS、Windows\u003C\u002Fli>\n\u003Cli>支持架构：x64（CUDA GPU 推荐）\u003C\u002Fli>\n\u003Cli>额外依赖：Python 3.10+、PyTorch 2.2+、可选 bitsandbytes\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"注意事项\">注意事项\u003C\u002Fh2>\u003Cul>\n\u003Cli>部分模型需要更新的 PyTorch 版本（如 MXFP4 量化需 2.6+）\u003C\u002Fli>\n\u003Cli>推荐使用 uv 管理依赖：\u003Ccode>uv run heretic\u003C\u002Fcode>\u003C\u002Fli>\n\u003Cli>仅用于合法的研究和教育目的\u003C\u002Fli>\n\u003C\u002Ful>\n",1790699397211]