This is the Linux app named StarSpace whose latest release can be downloaded as StarSpacesourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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StarSpace
DESCRIPTION
StarSpace is a general-purpose embedding-based learning framework that trains embeddings for entities (words, sentences, users, items) under various supervision signals (classification, ranking, matching). Instead of focusing on one task, StarSpace supports multi-task and multi-domain setups—for instance, you can train embeddings so that textual queries match item descriptions, sentences map to labels, or users align with liked items in the same embedding space. The training objective is contrastive: for a given query embedding, positive and negative examples are sampled and the model is optimized to score positive higher than negatives. The library supports a variety of tasks (text classification, nearest-neighbor search, recommendation, entity linking) with simple configuration. It includes efficient batching, negative sampling strategies, and on-the-fly embedding updates.
Features
- Contrastive embedding learning supporting classification, ranking, and matching
- Multi-domain capability: embeddings for users, items, queries, entities in unified space
- Efficient negative sampling and batching for scalable training
- Support for multiple task types (text classification, recommendation, entity linking)
- Command-line tools and configuration-driven workflows
- Examples and sample datasets for quick experimentation and adoption
Programming Language
C++
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/starspace.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
