Splade_PP_en_v1 is an ONNX and Transformers-compatible sparse embedding model developed for text classification, similarity searches, and retrieval-augmented generation. It is used with libraries such as FastEmbed and is maintained by the Qdrant team for integration into vector databases and search systems.
Splade PP En sits in PulseGate's Foundation models & chat category. It focuses on creating effective sparse vector representations for accurate semantic search and text similarity. It is built as an open-source project for developers. Splade PP En is open source under the Apache-2.0 license. The product ships for the web and API.
Qdrant builds and maintains Splade PP En, and the product first shipped in 2023. Development happens publicly on GitHub with 3.1k stars and 4 commits in the last 90 days. Key capabilities include Sparse Embeddings, Text Similarity, and FastEmbed Integration.
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