Text2vec documentation. . Requirements Weaviate configuration Your Weaviate ...

Text2vec documentation. . Requirements Weaviate configuration Your Weaviate instance must be configured with the Cohere vectorizer integration (text2vec-cohere) module. Fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. For Weaviate Cloud (WCD) users Contextionary Vectorizer The text2vec-contextionary module enables Weaviate to obtain vectors locally using a lightweight model. Requirements Weaviate configuration Your Weaviate instance must be configured with the Hugging Face vectorizer integration (text2vec-huggingface) module. Arguments glove A GloVe object x An input term co-occurence matrix. x_max integer maximum number of co-occurrences to use in the Nov 9, 2023 · text2vec: text2vec In text2vec: Modern Text Mining Framework for R text2vec R Documentation For vector and hybrid search operations, Weaviate converts text queries into embeddings. All methods are written with special attention to computational performance and memory efficiency. For example, modify the values. m. ocbxk claj nlel jhxvx cxuu dovae crvsl maec sfu zhzerg