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Embedding models, a crucial building block for retrieval systems, semantic search, and retrieval-augmented generation (RAG), are neural networks that convert documents into numerical vectors. Voyage-law-2 is a cutting-edge embedding model that is trained particularly for semantic retrieval of legal...
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Nomic Embed is the only truly open (open source, weights, and data) text embedder to beat OpenAI on both short and long context tasks.
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Embedding models, a crucial building block for retrieval systems, semantic search, and retrieval-augmented generation (RAG), are neural networks that convert documents into numerical vectors. voyage-large-2-instruct is a cutting-edge embedding model designed for general semantic retrieval tasks,...
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Twelve Labs multimodal foundation models create powerful vector embeddings that enable downstream applications. Our Marengo model understands video natively and is able to identify and interpret movements, actions, objects, individuals, sounds, on-screen text, and spoken words just like humans,...
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jina-embeddings-v2-base-code is an open-source coding embedding model supporting 8192 sequence length. This state-of-the-art AI embedding model enables many applications, such as code review, static analyses, documentation assistance, code search, or retrieval augmented generation (RAG).
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Cohere’s Classification Finetuning enables you to train and deploy classification models with a few lines of code. Using as few as 2 examples per label, users are able to train custom models to classify text based on semantic meaning (results will vary depending on the classification task at hand -...
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Jina Reranker v1 Turbo model is a neural text reranking model, designed to enhance the relevance of search results. This model is the best balance between accuracy and performance, offering fast and more memory-efficient reranking process. For our most accurate (and larger) reranker model,...
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The Universal Sentence Encoder encodes text into high-dimensional vectors that can be used for text classification, semantic similarity, clustering and other natural language tasks. The model is trained and optimized for greater-than-word length text, such as sentences, phrases or short...
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Nomic Embed Image is a state of the art image embedder that produces embeddings aligned to Nomic Embed Text, enabling multimodal extension of existing Nomic Embed Text applications.
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Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.
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