Cohere has introduced updates to its Embed model, supporting int8 and binary embeddings to reduce memory costs and increase efficiency. The new features include compressed embeddings and an updated Embed Jobs feature for large dataset processing.
This is a huge embedding announcement from Cohere with both int8 vectors AND binarized (1 bit per dimension). All versions are fully supported in @vespaengine, including the int8 version with angular distance and the binarized 1-bit version with hamming distance. https://t.co/oVwyKrTimG https://t.co/YECEi2B1my
Vastly superior Cohereโs embeddings are cheaper than OpenAI https://t.co/bgVZ7hTEy5
๐ ๐๐จ๐ก๐๐ซ๐ ๐๐ฆ๐๐๐ ๐๐ - ๐ข๐ง๐ญ๐ & ๐๐ข๐ง๐๐ซ๐ฒ ๐๐ฎ๐ฉ๐ฉ๐จ๐ซ๐ญ๐ I'm excited to launch our native support for int8 & binary embeddings for Cohere Embed V3. They slash your vector DB cost 4x - 32x while keeping 95% - 100% of the search quality. https://t.co/uJBg6nyPvf https://t.co/3TVabwKm52
Cohere announced an update for the Cohere Embed model, intended to reduce memory cost and increase efficiency. https://t.co/D0fokPzkZ8
Our Cohere Embed model now natively supports int8 and binary embeddings! Today, weโve released compressed embeddings and an updated Embed Jobs feature for error-free, efficient large dataset processing to support powerful enterprise search. https://t.co/acsnnvDKK8
Our Cohere Embed model now natively supports int8 and binary embeddings! Today, weโve released compressed embeddings and updated Embed Jobs feature for error-free, efficient large dataset processing to support powerful enterprise search. https://t.co/acsnnvDKK8
Our Cohere Embed model now natively supports int8 and binary embeddings! Today, weโve released new features including compressed embeddings and an updated Embed Jobs feature for error-free, efficient large dataset processing to support powerful enterprise search.โฆ