English word2vec embeddings trained on OpenSubtitles Part 4

This dataset contains the subs2vec embeddings for [Language Name], 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) sha256-hashes: en_300_1_cbow_wxd.csv.bz2 bb95d656d89d146d702d3c48d0661834c65d7e26b7fc2cc255b45490a22ad36d en_300_1_sg_wxd.csv.bz2 75a771cbcb5098cda48fcb8a0effae9f4612cd692b5c001fea0afbd36686fdd3 en_300_2_cbow_wxd.csv.bz2 0277f15afed8169677dfd9667644f98836f77792fac3aab8f725773034982915 en_300_2_sg_wxd.csv.bz2 d103ca78cd49d68a51515dbdf91746be8c471918865d1508f17cb892060b86b4 en_300_3_cbow_wxd.csv.bz2 fdbfbb039e3de5c22ba9ed29fdd5467029b59042cc74149c97cb60040fffaa68