Text analysis

Models 5

• Gen 7
  Rampart

  By National Design Studio

  Rampart is a 14.7 MB quantized ONNX token-classification model for client-side PII detection and redaction. Fine-tuned from MiniLM-L6-H384 with a 35-label BIO head covering 17 entity types, it supports 7 Latin-script languages. Designed to run in browsers via ONNX Runtime Web and Transformers.js at 6.6 ms p50 latency.

  🔒Data anonymization🔒Data protection📊Text analysis
  NewText

  Released 7d ago
• Gen 7 Rerank
  rerank 2.5

  By Voyage AI

  A reranking model that reorders search results to improve retrieval accuracy, with instruction-following capabilities to steer relevance scoring via natural language. Supports 32K token context length. Outperforms previous models and competing rerankers across multiple domains and languages.

  🔎Search📊Text analysis❓Question answering
  Text

  Released 10mo ago
• Gen 7 Rerank
  Rerank 2.5 lite

  By Voyage AI

  A latency-optimized reranker that refines retrieval results with instruction-following capabilities. Supports a 32K token context window, works across 31 languages, and outperforms larger open-source rerankers. Users can steer relevance scoring using natural language instructions appended to queries.

  🔎Semantic search🔍Information retrieval📊Text analysis
  Text

  Released 10mo ago
• Gen 7
  Voyage multilingual 2

  By Voyage AI

  Text embedding model optimized for multilingual retrieval and RAG. Supports 27 languages including French, German, Japanese, Spanish, Korean, and English, with a 32K token context window and 1024-dimensional embeddings. Outperforms OpenAI text-embedding-3-large and Cohere multilingual v3 on average across evaluated languages.

  🔎Semantic search📚Knowledge bases📄Document analysis📊Text analysis
  Text

  Released 2y ago
• Gen 7
  Voyage lite 01 instruct

  By Voyage AI

  Lightweight text embedding model fine-tuned on top of voyage-lite-01 for classification and clustering tasks. Features a 4096-token context window and 1024-dimensional output vectors. Not recommended for retrieval or search; classification and clustering are the only recommended use cases.

  📂Content categorization📊Text analysis
  Text

  Released 2y ago