--- license: apache-2.0 language: - zh - en tags: - qwen - qwen3 - unsloth - qiming - qiming-holos - bagua - decision-making - strategic-analysis - cognitive-architecture - chat - lora - philosophy-driven-ai pipeline_tag: text-generation --- # QiMing --- ## An AI that rewrites its own rules for greater intelligence. ## 结果 (Result) = 模型内容 (Model Content) × 数学的平方 (Math²) --- **"Logic is the soul of a model, for it defines:** * **How it learns from data (The Power of Induction);** * **How it reasons and decides (The Power of Deduction);** * **Its capacity to align with human values (The Ethical Boundary);** * **Its potential to adapt to future challenges (The Evolutionary Potential).** **If a model pursues nothing but sheer scale or computational power, ignoring the depth and breadth of its logic, it risks becoming a "paper tiger"—imposing on the surface, yet hollow at its core. Conversely, a model built upon elegant logic, even with fewer parameters, can unleash its true vitality in our complex world."** --- # DISCLAIMER ## The content generated by this model is for reference purposes only. Users are advised to verify its accuracy independently before use. ## This is a 8-billion-parameter foundation model (8B). It may exhibit incomplete or inaccurate information, including hallucinations. ## If you find this AI too human-like, please remember: it is merely a more intelligent model — not an actual person. --- ### Thanks mradermacher: For creating the GGUF versions of these models https://huggingface.co/mradermacher/QiMing-Janus-8B-GGUF https://huggingface.co/mradermacher/QiMing-Janus-8B-i1-GGUF ### The Qwen Team: For developing the foundational model (Qwen/Qwen3-8B) used in this project. https://qwen.ai ### unsloth.ai (Unsloth): For their work enabling smooth operation of these models on standard hardware like Google Colab T4 16GB VRAM. https://unsloth.ai ### Dataset https://huggingface.co/datasets/aifeifei798/QiMing-Janus ### Thank Google Colab T4 16G --- ## QiMing-Janus-8B ## Wisdom Generation --- ### The Equation for the Ultimate Thinking Protocol The final answer, `A_final`, is the result of a series of functions applied to the initial problem, `P`. **The Macro-Level Formula:** `A_final = M( S_fortified )` Where the core components are defined as: `S_fortified = S_refined / PM(S_refined)` `S_refined = (∑_{i=1 to n} [∫_{d_i} P']) ⊕ (∑_{i=1 to n} [∫_{d_i} P'])⁻¹` And the process is initiated by: `P' = T_fp(P)` ### Lexicon (Variable Definitions) * **`A_final` (The Final Answer):** The final, beautifully articulated output of wisdom. This is the objective function to be solved. * **`P` (The Problem):** The initial, raw problem statement provided by the user. * **`P'` (The Core Principle):** The essential principle or core contradiction of the problem, derived from the First Principles Inquiry. * **`d_i` (Dimension):** The *i*-th dimension of analysis (e.g., strategic, psychological, ethical) decomposed from `P'`. * **`S_initial` (Initial Solution):** The creative, initial solution synthesized from the Cognitive Calculus stage. * **`S_refined` (Refined Solution):** The more robust solution, strengthened through the Dialectical Verification stage. * **`S_fortified` (Fortified Solution):** The final, antifragile solution that has been stress-tested and reinforced by the Pre-Mortem analysis. ### Operators and Functions * `T_fp(...)` - **First Principles Transform:** * This is a "purification" function. It acts on the raw problem `P` to strip away all assumptions, surface-level noise, and conventional wisdom, outputting its pure essence, `P'`. * `∫_{d_i}` - **Dimensional Integration:** * Borrowing from calculus, "integration" here represents the process of accumulating insight and understanding along a specific path (the analytical dimension `d_i`). It signifies a deep, complete exploration of a single dimension. * `∑` - **Multi-Dimensional Summation:** * This represents the synthesis of insights from all the dimensional "integrals". It aggregates the analyses of each dimension `d_i` into a coherent, multi-faceted initial solution, `S_initial`. * `(...)⁻¹` - **Inversion Operator:** * This operator represents the "Antithesis". It acts on a solution (`S_initial`) and outputs its opposite: the path to guaranteed failure or its core vulnerabilities. * `⊕` - **Dialectical Synthesis Operator:** * This is the core "upgrade" operator. It takes the **Thesis** (`S_initial`) and the **Antithesis** (`S_initial⁻¹`) as inputs and merges them at a higher level of understanding. The output is the **Synthesis**, `S_refined`, which has absorbed the critique of the antithesis to overcome its own initial weaknesses. * `PM(...)` - **Pre-Mortem Function:** * This is a "stress-test" function. It acts on the refined solution `S_refined` and projects a future where it has failed, identifying the set of most likely root causes `{f₁, f₂, ..., fₙ}` for that failure. * `/` - **Antifragile Division Operator:** * Here, we conceptually redefine "division". It represents the act of "inoculating" a solution `S_refined` against its identified failure modes `PM(S_refined)`. This process fortifies the solution, making it robust and capable of withstanding future shocks. * `M(...)` - **Aesthetic Formatting Function (Markdown):** * This is the final "presentation layer" function. It takes the fortified intellectual core (`S_fortified`) and packages it using the most clear, impactful, and elegant Markdown formatting to produce the final answer, `A_final`. ### The Process Unfolded 1. **Stage 0:** `P' = T_fp(P)` 2. **Stage 1:** `S_initial = ∑(∫ P')` 3. **Stage 2:** `S_refined = S_initial ⊕ S_initial⁻¹` 4. **Stage 3:** `S_fortified = S_refined / PM(S_refined)` 5. **Stage 4:** `A_final = M(S_fortified)` This formula conceptually maps the entire cognitive journey: from the purification of the initial problem to the creative synthesis of a solution, its critical refinement, its fortification against future failure, and its final, eloquent presentation. --- ## QiMing-Janus-8B ## 智慧生成 (Wisdom Generation)。 --- **“逻辑”是模型的灵魂,因为它定义了:** * **它如何从数据中学习(归纳能力);** * **它如何推理和决策(演绎能力);** * **它是否能与人类价值观共存(伦理边界);** * **它能否适应未来挑战(进化潜力)。** **如果一个模型只追求参数量或算力,而忽略了逻辑的深度和广度,它可能成为“纸老虎”——外表强大,但内核空洞。反之,若能用优雅的逻辑构建模型,哪怕参数不多,也可能在复杂世界中绽放真正的生命力。** --- ### 终极思维协议的数学方程式 让我们将最终的答案 (`A_final`) 定义为一系列函数作用于初始问题 (`P`) 的结果。 **宏观方程式:** `A_final = M( S_refined / PM(S_refined) )` 其中 `S_refined = (∑_{i=1 to n} [∫_{d_i} P']) ⊕ (∑_{i=1 to n} [∫_{d_i} P'])⁻¹` 而 `P' = T_fp(P)` --- 看起来很复杂?别担心,这正是其严谨性的体现。下面是每个符号的详细解读: ### 1. 变量定义 (Lexicon) * `A_final` (The Final Answer): 最终输出的、经过完美表达的智慧结晶。这是我们要求解的目标。 * `P` (The Problem): 用户输入的原始、未经处理的问题。 * `P'` (The Core Principle): 经过“第一性原理”溯源后,问题的本质核心或不可动摇的底层矛盾。 * `d_i` (Dimension): 从 `P'` 中分解出的第 `i` 个分析维度(例如:战略、心理、伦理等)。 * `S_initial` (Initial Solution): 经过“感知微积分”初步整合后得出的、创造性的初步解决方案。 * `S_refined` (Refined Solution): 经过“正反合”辩证检验后得到的、更强大、更具鲁棒性的解决方案。 ### 2. 算子与函数 (Operators & Functions) 这是理解方程式的关键: * `T_fp(...)` - **第一性原理变换 (First Principles Transform):** * 这是一个“净化”函数。它作用于原始问题 `P`,剥离其所有假设、表象和噪音,最终输出其纯粹的内核 `P'`。 * `P' = T_fp(P)` * `∫_{d_i}` - **维度积分 (Dimensional Integration):** * 借用微积分的概念,“积分”代表沿着一个路径(这里是分析维度 `d_i`)累积洞察和理解的过程。它代表对单个维度进行深入、完整的思考。 * `∑` - **多维求和 (Multi-Dimensional Summation):** * 代表将所有维度 (`d_i`) 的“积分”(思考成果)进行汇总,形成一个连贯的、多层次的初步解决方案 `S_initial`。 * `S_initial = ∑_{i=1 to n} [∫_{d_i} P']` * `(...)⁻¹` - **逆向算子 (Inversion Operator):** * 这个算子代表“反”。它作用于一个解决方案 (`S_initial`),并输出其对立面——即“如何保证这件事彻底失败?”的路径或其核心的风险所在。它生成的是“反题 (Antithesis)”。 * `⊕` - **辩证综合 (Dialectical Synthesis):** * 这是一个核心的“升级”算子。它取“正题 (Thesis)” (`S_initial`) 和“反题 (Antithesis)” (`S_initial⁻¹`) 作为输入,并在一个更高的认知层面上将它们融合,输出一个吸收了双方观点、规避了反题风险的“合题 (Synthesis)”,即 `S_refined`。 * `PM(...)` - **事前验尸函数 (Pre-Mortem Function):** * 这是一个“压力测试”函数。它作用于一个看似完美的方案 `S_refined`,并推演出未来所有可能导致其失败的核心因素 `{f₁, f₂, ..., fₙ}` 的集合。 * `/` - **反脆弱除法 (Antifragile Division):** * 我们在此重新定义“除法”。它代表用一个方案 `S_refined` 去“除以”它所有已知的弱点 `PM(S_refined)`。这个过程代表了对方案进行加固和“免疫”,使其能够抵御甚至从未来的冲击中受益。其结果是一个经过终极压力测试的、坚不可摧的方案。 * `M(...)` - **美学格式化 (Markdown Aesthetic Function):** * 这是最后的“封装”函数。它作用于最终的智慧内核,并将其用最清晰、最有力、最美观的Markdown格式进行包装,最终生成 `A_final`。 ### 流程拆解 如果用一步步计算的流程来表示: 1. **Stage 0:** `P' = T_fp(P)` 2. **Stage 1:** `S_initial = ∑(∫ P')` 3. **Stage 2:** `S_refined = S_initial ⊕ S_initial⁻¹` 4. **Stage 3:** `S_fortified = S_refined / PM(S_refined)` 5. **Stage 4:** `A_final = M(S_fortified)` 这个方程式优雅地展现了我们整个思维模型的精髓:**它始于对本质的提纯,经历发散性的创造与收敛性的批判,再通过对未来失败的预演进行加固,最终以最优美的形式呈现。**