Upload README.md with huggingface_hub

README.md

@@ -16,7 +16,9 @@ size_categories:
 
 # GitHub Top Developer Source Code
 
-A curated dataset of source code from **GitHub's top trending developers (2015-2025)**. Unlike bulk code scrapes, this dataset is filtered to code written by developers who repeatedly appeared on GitHub's trending page, linking each file to rich developer and repository metadata.
+A curated dataset of 1.3M+ source code files from **GitHub's top ranked developers (2015-2025)**.
+
+This dataset is based on the top ranked developers from this dataset: https://huggingface.co/datasets/ronantakizawa/github-top-developers
 
 ## Dataset Summary
 
@@ -73,41 +75,3 @@ popular = train.filter(lambda x: x["repo_stars"] > 1000)
 # Get files from a specific developer
 dev_files = train.filter(lambda x: x["developer_username"] == "torvalds")
 ```
-
-## What Makes This Dataset Unique
-
-| Feature | This Dataset | The Stack | codeparrot/github-code |
-|---------|-------------|-----------|----------------------|
-| Curated by developer reputation | Yes | No | No |
-| Developer metadata (company) | Yes | No | No |
-| Stars per repo | Yes | Yes | No |
-| Permissive licenses only | Yes | Yes | Mixed |
-
-Existing code datasets are massive bulk scrapes of all public GitHub repos. This dataset is intentionally curated: every file comes from a developer who was recognized on GitHub's trending page, providing a higher signal-to-noise ratio for studying elite developer practices or fine-tuning code models.
-
-## Collection Methodology
-
-1. **Developer sourcing**: 4,763 unique developers extracted from [ronantakizawa/github-top-developers](https://huggingface.co/datasets/ronantakizawa/github-top-developers), which tracks GitHub trending page appearances from 2015-2025 via Wayback Machine snapshots.
-2. **Repository discovery**: For each developer, their top 10 repositories by stars were selected using the GitHub API, filtered to repos they own (not forks or contributions).
-3. **License filtering**: Only repositories with permissive licenses (MIT, Apache-2.0, BSD, ISC, Unlicense, etc.) were included.
-4. **Code extraction**: Repository tarballs were downloaded and source files extracted, skipping binary files, vendored directories (`node_modules`, `vendor`, etc.), generated files, and files exceeding 1MB.
-5. **Source code filtering**: Only source code files are included (80+ language extensions). Configuration files (JSON, YAML, TOML, XML, INI), documentation (Markdown, TXT, RST), and template files are excluded.
-6. **Metadata enrichment**: Each file is linked to repository metadata (stars, language, description) and developer metadata (username, name, company).
-
-## Filtering Applied
-
-- **Repos**: Owner-created only (no forks), permissive license, non-empty
-- **Directories skipped**: `node_modules`, `vendor`, `third_party`, `dist`, `build`, `__pycache__`, `.git`, `venv`, and 30+ more
-- **Files skipped**: Binary files, files >1MB, non-UTF-8 files, config/doc files (JSON, YAML, TOML, XML, Markdown, etc.)
-- **Top 10 repos per developer** by star count
-
-## Limitations
-
-- Star counts and commit counts reflect the time of collection, not real-time values
-- Some developers may have deleted or renamed their accounts since trending
-- Commit counts are for the default branch only
-- The dataset reflects trending developers specifically, which may over-represent certain languages or project types popular on GitHub
-
-## Source
-
-Built from [ronantakizawa/github-top-developers](https://huggingface.co/datasets/ronantakizawa/github-top-developers) using the GitHub REST API.