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Embeddings (82 results) showing 1 - 20
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ByCohere | Ver v1.0.9
Cohere's Rerank endpoint enables you to significantly improve search quality by augmenting traditional key-word based search systems with a semantic-based reranking system which can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers much higher quality... | |
ByCohere | Ver 1.0.9
Cohere's Rerank endpoint enables you to significantly improve search quality by augmenting traditional key-word based search systems with a semantic-based reranking system which can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers much higher quality... | |
ByCohere | Ver v2.0.3
Cohere's Rerank endpoint enables you to significantly improve search quality by augmenting traditional key-word based search systems with a semantic-based reranking system which can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers much higher quality... | |
ByCohere | Ver v3.3.12
Embed translates text and images into numerical vectors that models can understand. The most advanced generative AI apps rely on high-performing embedding models to understand the nuances of user inputs, search results, and documents. This Embed model has 1024 dimensions. | |
ByCohere | Ver v2.0.3
Cohere's Rerank endpoint enables you to significantly improve search quality by augmenting traditional key-word based search systems with a semantic-based reranking system which can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers much higher quality... | |
ByCohere | Ver v2.0.1 At Cohere, we are committed to breaking down barriers and expanding access to cutting-edge NLP technologies that power projects across the globe. By making our innovative multilingual language models available to all developers, we continue to move toward our goal of empowering developers,... | |
ByCohere | Ver v3.3.13
Embed 3 translates text and images into numerical vectors that models can understand. The most advanced generative AI apps rely on high-performing embedding models to understand the nuances of user inputs, search results, and documents. This Embed model has 1024 dimensions. This version is also a... | |
ByCohere | Ver v1.0.3
Cohere's Rerank endpoint enables you to significantly improve search quality by augmenting traditional key-word based search systems with a semantic-based reranking system which can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers much higher quality r... | |
ByCohere | Ver v3.3.12
Embed Light translates text and images into numerical vectors that models can understand. The most advanced generative AI apps rely on high-performing embedding models to understand the nuances of user inputs, search results, and documents. Embed Light is a smaller version of Embed with 384... | |
ByCohere | Ver v1.1.2
Cohere's Rerank v3.5 endpoint enables businesses to significantly improve search and retrieval-augmented generation systems. As input, it takes a query and list of potentially relevant documents. Rerank v3.5 then returns the documents as a list sorted by semantic similarity to the provided query.... | |
ByVoyage AI | Ver v1.0.1
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-large-2 is a cutting-edge embedding model... | |
ByJina AI | Ver 1.0 jina-colbert-reranker-v2 is multilingual ColBERT-based reranking model. ColBERT (Contextualized Late Interaction over BERT) leverages the deep language understanding of BERT while introducing a novel interaction mechanism. This mechanism, known as late interaction, allows for efficient and precise... | |
ByJina AI | Ver 1.3 jina-embeddings-v3 is a multilingual multi-task text embedding model designed for a variety of NLP applications. Based on the Jina-XLM-RoBERTa architecture, this model supports Rotary Position Embeddings to handle long input sequences up to 8192 tokens. Additionally, it features 5 LoRA adapters to... | |
ByVoyage AI | Ver v1.0.1
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-code-2 is optimized for retrieving code and... | |
ByJina AI | Ver 3.2 Jina Embeddings v2 Base model is optimized for highly accurate embeddings - For speed of inference and memory efficiency use the Small model. jina-embeddings-v2-base-en is an open-source English embedding model supporting 8192 sequence length. This state-of-the-art AI embedding model enables many a... | |
ByVoyage AI | Ver v1.0.1
Multimodal embedding models are neural networks that transform multiple modalities, such as text and images, into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality.... | |
ByUpstage | Ver v1.0.0
Solar Embedding Large is a powerful multilingual embedding model offering robust performance across multiple languages, including English, Korean, Japanese, and more. It's specifically fine-tuned for retrieval tasks, significantly enhancing multilingual retrieval results. This model is divided into... | |
ByWeaviate | Ver 1.24.8 Weaviate is a popular open-source low-latency vector database with out-of-the-box support for multimodal media types (text, images, etc.). The database stores both objects and vectors, allowing for combining vector search with structured filtering and the fault tolerance of a cloud-native database.... | |
ByVoyage AI | Ver v1.0.0
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-3-large is a state-of-the-art... | |
ByVoyage AI | Ver v1
Rerankers are neural networks that predict the relevancy scores between a query and documents and rank them based on the scores. They are used to refine search results in semantic search/retrieval systems and retrieval-augmented generation (RAG). rerank-lite-1 is a reranker optimized for both... |