LAP2-K-Think-v1.b


# **LAP2-K-Think-v1.b**

> **LAP2-K-Think-v1.b** is the refined continuation of the LAP2 reasoning series, curated by **prithivMLmods** and hosted on Hugging Face. This version expands the dataset to **~380K entries** and focuses heavily on **coding-based mathematical reasoning**, algorithmic logic, and structured step-wise problem solving. This dataset integrates a macro mixture of reasoning traces, combined with curated mathematical and computational reasoning tasks. Each example pairs a complex prompt with a detailed reasoning-based solution formatted for training advanced code-aware and reasoning-capable LLMs.

## Quick Start

```bash
pip install -U datasets
```

```python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/LAP2-K-Think-v1.b", split="train")
```

## Dataset Overview

| Attribute | Value |
| -------------------- | ---------------------------------------------------- |
| **Rows** | ~380,190 |
| **Size[partial]** | ~2.29 GB |
| **Format** | Parquet |
| **Language** | English |
| **License** | Apache-2.0 |
| **Focus Areas** | Code reasoning, algorithmic math, logic, computation |

## Structure

* **problem**: A coding, math, or mixed reasoning challenge
* **solution**: Structured and chain-of-thought style reasoning with final answer

---

## Source Inputs

Includes reasoning from:

* **Xen-Arc AI CodeX-2M-Thinking**: [Small traces, depending on the specific problem] Code-x structured programming logic, [XenArcAI/CodeX-2M-Thinking](https://huggingface.co/datasets/XenArcAI/CodeX-2M-Thinking)
* **Math-aligned custom prompts** : [Gargantua-R1-Wee](https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Wee)
* **Hybrid algorithmic reasoning tasks**: [Gargantua-R1-Wee](https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Wee)

## Use Cases

* Fine-tuning LLMs for programming reasoning
* Training models to think step-by-step before producing code
* Evaluation of reasoning alignment and computational logic
* Building tutoring or solver AI systems for coding and mathematics

## Maintainer

| Author | Last Updated |
| --------------------------------------------------------- | ------------ |
| **[prithivMLmods](https://huggingface.co/prithivMLmods)** | **Nov 2025** |


# **LAP2-K-Think-v1.b**

> **LAP2-K-Think-v1.b** 是 LAP2 推理系列的精修续作，由 **prithivMLmods** 整理并托管于 Hugging Face。该版本将数据集规模扩展至约38万条数据，核心聚焦于基于编码的数学推理、算法逻辑与结构化分步问题求解。本数据集整合了推理轨迹的宏观混合集，并搭配精选的数学与计算推理任务。每个样本均将复杂提示词与基于推理的详细解决方案配对，专为训练具备高级代码理解与推理能力的大语言模型（Large Language Model, LLM）设计。

## 快速上手

bash
pip install -U datasets

python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/LAP2-K-Think-v1.b", split="train")

## 数据集概览

| 属性名 | 值 |
| -------------------- | ---------------------------------------------------- |
| **数据行数** | 约380,190条 |
| **[部分]大小** | 约2.29 GB |
| **数据格式** | Parquet |
| **语言** | 英语 |
| **许可证** | Apache-2.0 |
| **核心领域** | 代码推理、算法数学、逻辑推理、计算 |

## 数据结构

* **problem**：涵盖编码、数学或混合推理挑战
* **solution**：采用结构化链式思维风格的推理过程，并包含最终答案

---

## 来源输入

包含来自以下数据源的推理轨迹：

* **Xen-Arc AI CodeX-2M-Thinking**：[针对特定问题的小型推理轨迹] 采用代码-x结构化编程逻辑，详见 [XenArcAI/CodeX-2M-Thinking](https://huggingface.co/datasets/XenArcAI/CodeX-2M-Thinking)
* **数学对齐自定义提示词**：详见 [Gargantua-R1-Wee](https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Wee)
* **混合算法推理任务**：详见 [Gargantua-R1-Wee](https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Wee)

## 应用场景

* 面向编程推理的大语言模型微调
* 训练模型在生成代码前进行分步思考
* 评估推理对齐性与计算逻辑能力
* 构建面向编码与数学的辅导或求解AI智能体（AI Agent）系统

## 维护者

| 作者 | 最后更新时间 |
| --------------------------------------------------------- | ------------ |
| **[prithivMLmods](https://huggingface.co/prithivMLmods)** | **2025年11月** |