vector-store
scandi-wiki-vector-store
Dataset Card for kardosdrur/scandi-wiki-vector-store
This dataset was created using the vicinity library, a lightweight nearest neighbors library with flexible backends.
It contains a vector space with 3655450 items.
Usage
You can load this dataset using the following code:
from vicinity import Vicinity
vicinity = Vicinity.load_from_hub("kardosdrur/scandi-wiki-vector-store")
After loading the dataset, you can use the vicinity.query method to find the nearest neighbors to… See the full description on the dataset page: https://huggingface.co/datasets/kardosdrur/scandi-wiki-vector-store.ontology-sqlite-vectorstore
Ontology & Embedding Database
This repository provides the local ontology database to be used by StructSense (in general can be used for any other purpose), including both structured ontological data and precomputed vector embeddings for efficient semantic search.
Overview
3,925,124 classes
2,683,756 synonyms
Data storage:
SQLite → structured ontology data (bioportal.db)
Embeddings → vector embeddings (to be uploaded)
Vector embeddings (includes preferred label +… See the full description on the dataset page: https://huggingface.co/datasets/sensein/ontology-sqlite-vectorstore.product-vectorstorevectorstore-mental_health
Vectorstore Dataset: Mental Health
Overview
This dataset contains pre-computed vector embeddings for the mental health domain, ready for use in Retrieval-Augmented Generation (RAG) applications, semantic search, and knowledge base systems. The embeddings are generated from high-quality source documents using state-of-the-art sentence transformers, making it easy to build production-ready RAG applications without the computational overhead of embedding generation.… See the full description on the dataset page: https://huggingface.co/datasets/meetara-lab/vectorstore-mental_health.vectorstore-women_health
Vectorstore Dataset: Women Health
Overview
This dataset contains pre-computed vector embeddings for the women health domain, ready for use in Retrieval-Augmented Generation (RAG) applications, semantic search, and knowledge base systems. The embeddings are generated from high-quality source documents using state-of-the-art sentence transformers, making it easy to build production-ready RAG applications without the computational overhead of embedding generation.… See the full description on the dataset page: https://huggingface.co/datasets/meetara-lab/vectorstore-women_health.vectorstore-accounting
Vectorstore Dataset: Accounting
Overview
This dataset contains pre-computed vector embeddings for the accounting domain, ready for use in Retrieval-Augmented Generation (RAG) applications, semantic search, and knowledge base systems. The embeddings are generated from high-quality source documents using state-of-the-art sentence transformers, making it easy to build production-ready RAG applications without the computational overhead of embedding generation.… See the full description on the dataset page: https://huggingface.co/datasets/meetara-lab/vectorstore-accounting.