babylonhealth/fastText_multilingual resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1201 stars · 120 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of 78 alignment matrices that project Facebook's monolingual fastText word vectors into a single shared multilingual vector space, based on an ICLR 2017 paper. It includes Jupyter notebooks for using the matrices and learning your own alignments, enabling cross-lingual word translation prediction.

Use cases

• align word vectors from different languages into one shared space
• predict translations of words across languages without a bilingual dictionary
• build multilingual NLP models with cross-lingual embeddings
• compare word similarity across languages like French and Russian
• learn custom alignment matrices for new language pairs
• zero-shot cross-lingual word translation for language pairs without training data

When to choose

• you need cross-lingual word embeddings for the original fastText 90 languages
• you want to do zero-shot word translation between language pairs without bilingual dictionaries
• you need monolingual fastText behavior preserved while gaining multilingual alignment
• you want to reproduce or extend the ICLR 2017 bilingual word vectors research

When to avoid

• you need actively maintained tooling or support
• you need alignment for languages beyond the original fastText 90 (e.g., the newer 204 languages)
• you need sentence-level or contextual embeddings rather than static word vectors
• you want a turnkey multilingual model rather than raw matrices plus fastText vectors

Facets

dataset · maturity abandoned

nlp machine-learning serialization machine-learning python cross-platform word-embeddings word-vectors fasttext multilingual cross-lingual-embeddings translation svd-alignment pretrained-models natural-language-processing algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="babylonhealth/fastText_multilingual")