SentenceTransformer based on intfloat/multilingual e5 large This is a sentence transformers model finetuned from intfloat/multilingual e5 large on an augmented version of stsb multi es dataset. It maps sentences & paragraphs to a 1024 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: intfloat/multilingual e5 large Maximum Sequence Length: 512 tokens Output Dimensionality: 1024 tokens Similarity Function: Cosine Similarity Training Dataset: stsb multi es aug 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 Evaluation Metrics Semantic Similarity Dataset: sts dev 768 Evaluated with EmbeddingSimilarityEvaluator Metric Value : : pearson cosine 0.8382 spearman cosine 0.843…
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