llm-jp/scripts
Jan 2025 – Jul 2025
2 Months active
Languages Used
BashPythonShell
Technical Skills
Command-line Interface (CLI)Data FilteringData ProcessingDataset ManagementFile HandlingMultiprocessing
Kouta Nakayama
PROFILE
Kouta Nakayama
Worked on the llm-jp/scripts repository to deliver robust data preprocessing tools and improve dataset management workflows. Developed Python scripts for score-based splitting and duplicate document filtering, enabling scalable, multiprocessing-powered pipelines for the fineweb-edu corpus and outputting results in efficient formats like JSONL.GZ. Enhanced usability by providing installation instructions and usage examples, supporting data engineering teams in managing large datasets. Addressed installation reliability by fixing broken JGLUE dataset URLs and updating references across Python and shell scripts, ensuring smooth onboarding and CI stability. Demonstrated proficiency in Python, shell scripting, multiprocessing, and file handling to streamline data processing and setup.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
458
Activity Months2
Your Network
2 peopleSame Organization
@nii.ac.jp1
Masaharu HayashiMember
Shared Repositories
1
Work History
July 2025
1 Commits
Jul 1, 2025July 2025 monthly summary for llm-jp/scripts focused on installer reliability and dataset handling. Implemented a critical fix to the JGLUE dataset URL to resolve installation errors and ensure reliable downloads during setup, addressing issue #88. Changes streamlined the onboarding experience and contributed to CI stability for the project.
1 Commits
Jul 1, 2025July 2025 monthly summary for llm-jp/scripts focused on installer reliability and dataset handling. Implemented a critical fix to the JGLUE dataset URL to resolve installation errors and ensure reliable downloads during setup, addressing issue #88. Changes streamlined the onboarding experience and contributed to CI stability for the project.
July 2025
January 2025
2 Commits • 2 Features
Jan 1, 20252025-01 monthly summary: Delivered two data-preprocessing features in llm-jp/scripts that directly enable scalable, high-quality data pipelines. Feature 1 adds a score-based splitting script for the fineweb-edu-score-2 corpus with configurable split factors, cache sizing, and multiprocessing, improving throughput and storage efficiency. Feature 2 adds a duplicate-document filtering script that cross-checks against the fineweb-edu corpus, processes parquet inputs, and outputs unique documents in JSONL.GZ; includes installation instructions and usage examples with multiprocessing. No major bug fixes reported this month. Overall, the work enhances data quality and processing speed, reducing downstream model training time and enabling more reliable analytics. Skills demonstrated include Python scripting, multiprocessing, parquet/JSONL.GZ handling, and doc generation.
January 2025
2 Commits • 2 Features
Jan 1, 20252025-01 monthly summary: Delivered two data-preprocessing features in llm-jp/scripts that directly enable scalable, high-quality data pipelines. Feature 1 adds a score-based splitting script for the fineweb-edu-score-2 corpus with configurable split factors, cache sizing, and multiprocessing, improving throughput and storage efficiency. Feature 2 adds a duplicate-document filtering script that cross-checks against the fineweb-edu corpus, processes parquet inputs, and outputs unique documents in JSONL.GZ; includes installation instructions and usage examples with multiprocessing. No major bug fixes reported this month. Overall, the work enhances data quality and processing speed, reducing downstream model training time and enabling more reliable analytics. Skills demonstrated include Python scripting, multiprocessing, parquet/JSONL.GZ handling, and doc generation.
Activity
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Quality Metrics
Correctness96.6%
Maintainability93.4%
Architecture93.4%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashPythonShell
Technical Skills
Command-line Interface (CLI)Data FilteringData ProcessingDataset ManagementFile HandlingMultiprocessingPythonScriptingShell Scripting
Repositories Contributed To
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