SentenceTransformer based on dbmdz/bert base turkish uncased This is a sentence transformers model finetuned from dbmdz/bert base turkish uncased on the cleaned turkish embedding model training data colab dataset. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. Model Details Model Description Model Type: Sentence Transformer Base model: dbmdz/bert base turkish uncased Maximum Sequence Length: 512 tokens Output Dimensionality: 768 dimensions Similarity Function: Cosine Similarity Training Dataset: cleaned turkish embedding model training data colab Model Sources Documentation: Sentence Transformers Documentation Repository: Sentence Transformers on GitHub Hugging Face: Sentence Transformers on Hugging Face Full Model Architecture Usage Direct Usage (Sentence Transformers) First install the Sentence Transformers library: Then you can load this model and run inference. c++\n include \nad alanı std\'sini kullanma;\n \nint ana() {\n //Kullanıcıdan adını girmesini isteyin\n cout y == true, x)/length( x)) 100; rakam=2) end 1:size... İşte bi…
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