German word2vec embeddings trained on OpenSubtitles Part 3

This dataset contains the subs2vec embeddings for German, as presented in https://zenodo.org/records/17243814. The embeddings were trained on large-scale subtitle corpora and represent semantic vector spaces derived from naturalistic language use in films and television from the OpenSubtitles 2018 datasets: https://opus.nlpl.eu/OpenSubtitles/corpus/version/OpenSubtitles. 

For this language, we provide all embedding variants explored in the study. Specifically, the dataset includes vectors generated under different combinations of:

• Dimensionality: multiple vector sizes (e.g., 100, 200, 300, …)
• Window size: varying context windows (e.g., 2, 5, 10, …)
• Each file corresponds to a unique configuration (dimension × window size). 

Each file contains the vocabulary for that language (column 1) and then the embedding values (columns 2 through dimension size + 1). 

If you use this dataset, please cite:

• Manuscript: https://doi.org/10.5281/zenodo.17243812 
• Data: This Zenodo dataset (using the DOI provided here)

Some files were split into parts due to limitations with Zenodo: 

• If you’ve downloaded files named like file.bz2.part_000, file.bz2.part_001, etc., you’ll need to recombine them before use.
• Please download and use the README file, which explains how to download, recombine, and verify the split files (for Linux, Mac, and Windows). 
• Windows users will need to download our helper file FileChunker.ps1. 

sha256sum hash values for verification:

• 4047c670d6556c3f7548bbb27ee63a2243588d6bd440a22e3a3140682c8f0a09  de_500_3_sg_wxd.csv.bz2