ClimSocAna/tecb-de
German Text Embedding Clustering Benchmark
This project helps researchers and data scientists evaluate how well different language models can group German texts by meaning or topic. It takes various German text datasets (like book titles, news articles, or Reddit posts) and assesses how accurately a given model can cluster them into their predefined categories. This is designed for anyone working with German language data who needs to understand and compare the performance of text embedding models for clustering tasks.
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Use this if you are a researcher or data scientist evaluating or developing natural language processing models for German text clustering and need benchmark datasets and results.
Not ideal if you are looking for a ready-to-use tool to cluster your own German texts without evaluating different underlying models.
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18
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1
Language
Python
License
MIT
Category
Last pushed
Mar 15, 2024
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