SentenceTransformer based on sentence transformers/all mpnet base v2 This is a sentence transformers model finetuned from sentence transformers/all mpnet base v2. 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: sentence transformers/all mpnet base v2 Maximum Sequence Length: 384 tokens Output Dimensionality: 768 tokens Similarity Function: Cosine Similarity 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. Click to see the direct usage in Transformers Click to expand Training Details Training Dataset Unnamed Dataset Size: 300,000 training samples Columns: sentence1 , sentence2 , and score Approximate statistics based on the first 1000 samples: sentence1 sentence2 score : : : : type string…
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