Castilian MT
Translation into Spanish from Spain (es-ES) with MADLAD-400: model, data and Spain vs Latin America labels.
Translation • 3B • Updated • 13Note Start here. MADLAD-400-3B-MT fine-tuned to translate into Castilian Spanish (vosotros, móvil, ordenador, coche, zumo…) with the target tag <2es_ES>. v4 on main (recommended); v1 (most systematic Castilian choices) and v3 on branches. Use transformers 4.x.
Ugiat/madlad400-3b-mt-es_ES-ct2
Translation • Updated • 12Note The same model converted to CTranslate2 int8 (2.9 GB): faster and lighter, for production translation on GPU or CPU.
Ugiat/madlad-400-es_ES-backtranslated
Viewer • Updated • 1.18M • 48Note 1.18M translation pairs from 8 languages (en, fr, pt, ca, it, de, gl, eu) into Castilian, built by back-translation: the Castilian side is real text from Spain. The training data of the model.
Ugiat/madlad-400-es_ES-sentences
Viewer • Updated • 18.9M • 527Note 18.7M clean sentences of Spanish as written in Spain (438M words), selected from MADLAD-400's Spanish split, each tagged with the Castilian features it contains.
Ugiat/madlad-400-es-annotations
Viewer • Updated • 266M • 2.01kNote Spain vs Latin America scores, dialect markers, languages and website scores for all 250.9M documents of MADLAD-400's Spanish split; castilian_selected marks the 70.1M documents used for the sentences.
Ugiat/spanish-variety-fasttext
Text Classification • Updated • 57Note Fast document classifier: Spain (es_ES) vs Latin America (es_LATAM). It produced the scores in the annotations dataset. For documents, not single sentences.
google/madlad400-3b-mt
Translation • 3B • Updated • 148k • 245Note Upstream: the original multilingual translation model this work fine-tunes (Google).
Note The sister model for Latin American Spanish (es-419).
allenai/MADLAD-400
Updated • 239k • 184Note Upstream: the web corpus all the Castilian data was selected from (Google, distributed by AllenAI).
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
Paper • 2309.04662 • Published • 26Note Upstream: the MADLAD-400 paper (Kudugunta et al., 2023), which introduced both the corpus and the base model.