modernbert embed base trained on triplets This is a sentence transformers model finetuned from nomic ai/modernbert embed base. 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: nomic ai/modernbert embed base Maximum Sequence Length: 8192 tokens Output Dimensionality: 768 dimensions Similarity Function: Cosine Similarity Language: en License: apache 2.0 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 Triplet Dataset: dev Evaluated with TripletEvaluator Metric Value : : cosine accuracy 0.9959 Triplet Dataset: dev Evaluated with TripletEvaluator Metric Value : : cosine accuracy 0.9939 Training Details Training D…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy