March 7, 2024, 6:30 a.m. | Pragati Jhunjhunwala

MarkTechPost www.marktechpost.com

Salesforce AI Researchers introduced the SFR-Embedding-Mistral model to address the challenge of improving text-embedding models for various natural language processing (NLP) tasks, including retrieval, clustering, classification, and semantic textual similarity. The existing models have shown state-of-the-art performance in certain tasks; there is a chance for advancements to achieve better performance across diverse benchmarks. Current text-embedding […]


The post Salesforce AI Research Introduces the SFR-Embedding Model: Enhancing Text Retrieval with Transfer Learning appeared first on MarkTechPost.

ai research ai researchers art challenge chance classification clustering editors pick embedding embedding models language language processing mistral natural natural language natural language processing nlp performance processing research researchers retrieval salesforce salesforce ai semantic staff state tasks tech news text textual transfer transfer learning

More from www.marktechpost.com / MarkTechPost

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne