NickIBrody/x86-asm-instructions-23k
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--- license: other task_categories: - text-generation language: - en tags: - code - assembly - x86 - x86-64 - instruction-tuning - code-generation size_categories: - 10K<n<100K pretty_name: x86 ASM Instructions - 23K --- # x86 ASM Instructions - 23K Instruction-tuning dataset of x86 and x86_64 assembly snippets paired with short natural-language instructions or comments. ## Dataset Summary | Field | Value | |---|---| | Total rows | 23,104 | | Split(s) | train | | Format | JSONL (`instruction`, `output`, `system`) | | Instruction average length | 47.0 characters | | Instruction max length | 413 characters | | Output average length | 514.25 characters | | Output max length | 15,805 characters | | System prompt values | 1 | ## Format Each example contains: ```json { "instruction": "Recursive factorial. cdecl calling convention.", "output": "factorial_rec_cdecl:\n enter 0, 0\n ...", "system": "As an x86/x86_64 assembly expert, you are capable of writing optimized low-level code from specifications." } ``` ## Recommended Use - supervised fine-tuning for x86 or x86_64 assembly generation - low-level code completion experiments - instruction-to-assembly research with additional downstream filtering ## Important Limitations - the dataset currently exposes only a `train` split - instructions vary in quality and appear to include extracted comments, partial descriptions, and terse labels rather than consistently written prompts - the dataset appears to mix multiple domains including general assembly routines, DOS-era utilities, boot-related code, and potentially malware-adjacent samples - examples are standalone snippets and often rely on missing surrounding context such as memory layout, calling convention, macro definitions, or target platform - the `system` field is constant across rows and may be better injected by the training template instead of consumed as sample data ## Safety Note This dataset appears to include low-level code related to file infection, boot manipulation, destructive disk access, or other malware-adjacent behavior in at least some samples. Downstream users should review and filter the corpus before production use, safety-sensitive training, or redistribution. ## Provenance And Licensing This release does not currently document per-example provenance fields such as repository, source file, commit, or source license. Because of that, this dataset should not be treated as a clean permissively licensed corpus without further legal and provenance review. ## Missing Metadata The current release still lacks: - repository / file / commit provenance - per-example source license metadata - domain labels such as `bootloader`, `dos`, `utility`, `malware`, or `reversing` - validation and test splits - contamination analysis against downstream benchmarks ## Suggested Next Steps To make this dataset more useful, the next revision should add: 1. deterministic `validation` and `test` splits 2. provenance fields for each sample 3. filtering or explicit labeling for malware-adjacent content 4. instruction-quality filtering for short or fragmentary prompts
license: 其他 task_categories: - 文本生成 language: - 英语 tags: - 代码 - 汇编 - x86 - x86-64 - 指令微调（instruction-tuning） - 代码生成 size_categories: - 10K<n<100K pretty_name: x86汇编指令集-23K # x86汇编指令集-23K 本数据集为x86与x86-64汇编代码片段数据集，配套简短自然语言指令或注释，用于指令微调（instruction-tuning）。 ## 数据集概述 | 字段 | 取值 | |---|---| | 总行数 | 23,104 | | 划分集 | 训练集 | | 格式 | JSONL格式，包含`instruction`、`output`、`system`字段 | | 指令平均长度 | 47.0个字符 | | 指令最大长度 | 413个字符 | | 输出平均长度 | 514.25个字符 | | 输出最大长度 | 15,805个字符 | | System提示词取值数量 | 1 | ## 样本格式 每个样本包含以下内容： json { "instruction": "递归阶乘，采用cdecl调用约定（cdecl calling convention）。", "output": "factorial_rec_cdecl: enter 0, 0 ...", "system": "作为一名x86/x86-64汇编专家，您能够根据规范编写优化后的底层代码。" } ## 推荐用途 - 用于x86或x86-64汇编代码生成的监督微调 - 底层代码补全实验 - 结合下游过滤的指令转汇编研究 ## 重要限制 - 该数据集目前仅提供训练集划分 - 指令质量参差不齐，包含提取的注释、部分描述与简洁标签，而非统一规范的提示词 - 数据集涵盖多个领域，包括通用汇编例程、DOS时代工具、启动相关代码，以及潜在的恶意软件关联样本 - 样本均为独立代码片段，通常依赖缺失的上下文信息，如内存布局、调用约定、宏定义或目标平台 - 所有样本的`system`字段均为固定值，更适合通过训练模板注入，而非作为样本数据直接使用 ## 安全提示 本数据集的部分样本包含与文件感染、启动项修改、破坏性磁盘访问或其他恶意软件关联行为相关的底层代码。下游使用者在投入生产使用、进行安全敏感的训练或重新分发前，应先对数据集进行审查与过滤。 ## 来源与许可 本次发布未记录每个样本的来源字段，如代码仓库、源文件、提交记录或源许可证。 因此，未经进一步的法律审查与来源验证，该数据集不应被视为干净的宽松许可语料库。 ## 缺失的元数据 当前版本仍缺少以下内容： - 代码仓库/文件/提交来源信息 - 每个样本的源许可证元数据 - 领域标签，如`bootloader`（引导加载程序）、`dos`（DOS系统）、`utility`（工具程序）、`malware`（恶意软件）或`reversing`（逆向工程） - 验证集与测试集划分 - 针对下游基准测试的污染分析 ## 建议后续改进方向 为提升该数据集的实用性，下一版应补充以下内容： 1. 确定的验证集与测试集划分 2. 每个样本的来源字段 3. 对恶意软件关联内容进行过滤或明确标注 4. 对过短或碎片化的提示词进行指令质量过滤
