AI search engine

E5-mistral-7b-instruct is a text embedding model with 32 layers and 4096 embedding sizes. It can be used to encode queries and documents to produce semantic vector representations. The model uses natural language task descriptions to guide the text embedding process and can be customized for different tasks. The model was trained on the MS-MARCO passage ranking dataset and can be used for natural language processing tasks such as information retrieval and question answering.

Haystack is an end-to-end natural language processing framework that helps you build applications powered by LLMs, Transformer models, vector search, and more. Whether you want to do question answering, answer generation, semantic document search, or build tools capable of complex decision-making and query solving, use Haystack's state-of-the-art NLP models to build end-to-end NLP applications that solve your use cases.