This release packages the current me_fasttext prototype as a citable research
artifact for readers of the accompanying arXiv paper.
- FastText-compatible C++ training and inference commands.
- Exact trie-based word and character n-gram ids.
- Legacy trie traversal and row sharing. A subsequent source audit found norm-ratio checks rather than the paper's cosine criterion, with hardcoded 128-dimensional loops.
- Mark-compact export into a single mmap serving index (
<output>.z). - Helper tools for compact-index generation and n-gram inspection.
- Benchmark protocol and benchmark issue template for external reports.
- Evaluator quickstart for turning a first clone into a useful benchmark report.
bench_ftindexfor compact.zretrieval/OOV serving measurements.- Retrieval comparison matrix for FastText, BM25, dense embedding, reranker, and vector-search comparisons.
- Artifact card for quick citation, benchmark, and list-maintainer triage.
- Citation metadata for GitHub and reference managers.
Use this release as a starting point for memory-sensitive FastText-style embedding experiments, large-vocabulary lexical retrieval, OOV-heavy text features, and mmap serving investigations.
This is not presented as a drop-in replacement for transformer embedding models or a complete RAG framework. It is a compact lexical memory layer that can be used alongside modern retrieval and reranking systems.
For readers approaching the project from efficient inference, FastText, word embeddings, double-array tries, retrieval systems, or memory-management backgrounds, see:
- Compact inference note: https://github.com/initial-d/me_fasttext/blob/main/docs/inference_optimization_note.md
- Evaluator quickstart: https://github.com/initial-d/me_fasttext/blob/main/docs/evaluator_quickstart.md
- Cross-community positioning: https://github.com/initial-d/me_fasttext/blob/main/docs/cross_community_positioning.md
- Artifact card: https://github.com/initial-d/me_fasttext/blob/main/docs/artifact_card.md
- Retrieval and OOV serving benchmark: https://github.com/initial-d/me_fasttext/blob/main/docs/retrieval_oov_benchmark.md
- Retrieval comparison matrix: https://github.com/initial-d/me_fasttext/blob/main/docs/retrieval_comparison_matrix.md
- Linux is the tested target.
- Rebuild binaries on the target machine before production use.
- Compression and latency depend on corpus, vocabulary, n-gram settings, hardware, filesystem, and OS page-cache behavior.