SentenceTransformer based on google/embeddinggemma 300m This is a sentence transformers model finetuned from google/embeddinggemma 300m. 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: google/embeddinggemma 300m Maximum Sequence Length: 2048 tokens Output Dimensionality: 768 dimensions 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: 1,000 training samples Columns: anchor , positive , and negative Approximate statistics based on the first 1000 samples: anchor positive negative : : : : type string string string details min: 9 tokens m…
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