Datasets:

EmergentMethods
/

en_qdrant_wikipedia

Tasks:

Feature Extraction

Modalities:

Formats:

Languages:

Size:

Tags:

sparse-embeddings

vector-database

Libraries:

License:

Dataset card Data Studio Files Files and versions

rcaulk commited on Sep 4, 2025

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b7e1967

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1 Parent(s): 93e1e68

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@@ -19,8 +19,9 @@ size_categories:
 # Wikipedia English Embeddings Dataset (Qdrant Snapshot)
-This dataset contains a complete [Qdrant vector database](https://qdrant.tech/) snapshot of Wikipedia English articles with both SPLADE and BM25 sparse embeddings for advanced semantic search capabilities.
 ## Dataset Details
 ### Dataset Description
@@ -350,7 +351,7 @@ Users should be aware of these limitations and consider:
 - **Qdrant**: Version 1.15+ recommended
 - **Python Dependencies**: `qdrant-client`, `fastembed`, `python-dotenv`
-- **Hardware**: Minimum 16GB RAM recommended for optimal performance
 - **Storage**: Approximately 380GB for the complete database
 ## Citation

 # Wikipedia English Embeddings Dataset (Qdrant Snapshot)
+![Qdrant Wiki](./logo.png)
+This dataset contains a complete [Qdrant vector database](https://qdrant.tech/) snapshot of Wikipedia English articles, each chunked and embedded with both SPLADE and BM25 sparse embeddings, yeilding a total of 130M embeddings. Chunks are linked to their neighbors and the main text to make full context retrieval simple and fast.
 ## Dataset Details
 ### Dataset Description
 - **Qdrant**: Version 1.15+ recommended
 - **Python Dependencies**: `qdrant-client`, `fastembed`, `python-dotenv`
+- **Hardware**: Minimum 12GB RAM recommended
 - **Storage**: Approximately 380GB for the complete database
 ## Citation