GermanWordEmbeddings There has been a lot of research about the training of word embeddings on English corpora. This toolkit applies gensim's word2vec on German corpora to train and evaluate German word embeddings. An overview about the project, evaluation results and download links can be found on the project's website or directly in this repository. [!NOTE] This project is old (2015) and trained word embeddings on German text long before LLMs were called AI. I still actively maintain this repo, the models from the past still load and can be used.
| Stars | 245 |
| Forks | 51 |
| Language | Jupyter Notebook |
| Category | LLM 插件 |
| License | MIT |
| Quality Score | 64.5207077341083/100 |
| Last Updated | 2026-10-07 |
| Created | 2015-05-22 |
| Est. Tokens | ~19k |
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GermanWordEmbeddings is Toolkit to obtain and preprocess German text corpora, train models and evaluate them with generated testsets. Built with Gensim and Tensorflow.. It is categorized as a LLM 插件 with 245 GitHub stars.
GermanWordEmbeddings is primarily written in Jupyter Notebook. It covers topics such as deep-learning, deep-neural-networks, gensim.
You can find installation instructions and usage details in the GermanWordEmbeddings GitHub repository at github.com/devmount/GermanWordEmbeddings. The project has 245 stars and 51 forks, indicating an active community.
GermanWordEmbeddings is released under the MIT license, making it free to use and modify according to the license terms.