German Semantic STS V2 Note: Check out my new, updated models: German Semantic V3 and V3b! This model creates german embeddings for semantic use cases. This is a sentence transformers model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search. Special thanks to deepset for providing the model gBERT large and also to Philip May for the Translation of the dataset and chats about the topic. Model score after fine tuning scores best, compared to these models: Model Name Spearman xlm r distilroberta base paraphrase v1 0.8079 xlm r 100langs bert base nli stsb mean tokens 0.7877 xlm r bert base nli stsb mean tokens 0.7877 roberta large nli stsb mean tokens 0.6371 T Systems onsite/ german roberta sentence transformer v2 0.8529 paraphrase multilingual mpnet base v2 0.8355 T Systems onsite/ cross en de roberta sentence transformer 0.8550 aari1995/German Semantic STS V2 0.8626 Usage (Sentence Transformers) Using this model becomes easy when you have sentence transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) Without sentence transformers, you can use the model like this…
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