sentence-transformers /

all-MiniLM-L12-v2

3 DZD in / 1M tokens

all-MiniLM-L12-v2 is a widely used, highly efficient sentence embedding model developed by Sentence Transformers. Based on the 33.4-million parameter microsoft/MiniLM-L12-H384-uncased architecture, it maps sentences and short paragraphs into a dense 384-dimensional vector space. Fine-tuned on over 1 billion sentence pairs using self-supervised contrastive learning, it offers an excellent balance between retrieval speed, memory footprint, and semantic accuracy, making it a foundational baseline for lightweight semantic search and clustering applications.