Romanian word2vec embeddings trained on OpenSubtitles Part 2
Description
This dataset contains the subs2vec embeddings for Romanian, 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)
Files
Files
(3.8 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:cac0a7514fe7069909057e42e6b332b1
|
1.9 GB | Download |
|
md5:1ce20479288c3db94e18e7d4a697ba89
|
1.9 GB | Download |
Additional details
Related works
- Is supplemented by
- Standard: 10.5281/zenodo.17243812 (DOI)
Software
- Repository URL
- https://github.com/SemanticPriming/word2manylanguages
- Programming language
- Python , R