Cohere Embed v3 English
Version: 1
Cohere Embed English is the market’s leading multimodal (text, image) representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering. Embed English has top performance on the HuggingFace MTEB benchmark and performs well on a variety of industries such as Finance, Legal, and General-Purpose Corpora.The model was trained on nearly 1B English training pairs.
Content Filtering
Prompts and completions are passed through a default configuration of Azure AI Content Safety classification models to detect and prevent the output of harmful content. Learn more about Azure AI Content Safety . Configuration options for content filtering vary when you deploy a model for production in Azure AI; learn more .Evaluation results can be found in the following Embed v3.0 BEIR Evaluation Results and full MTEB results can be found in the following Embed v3.0 MTEB Evaluation Results . Evaluations against multi-modal embedding models can be found in the following Embed v3.0 Multimodal Evaluation Results .
Model Specifications
Context Length512
LicenseCustom
Last UpdatedApril 2024
Input TypeText
Output TypeEmbeddings
PublisherCohere
Languages1 Language