# Large-scale Transformer

A 500M-parameter Transformer model pre-trained on the human reference genome, integrating DNA sequence information from over 3,200 diverse human genomes and 850 species

Pythia-6.9B is a large-scale language model developed by EleutherAI, part of the Pythia scalable suite, specifically designed to facilitate interpretability research.

A large-scale multilingual speech recognition model introduced by Meta AI, supporting 60 languages, based on a 1-billion-parameter Transformer encoder architecture.

BigScience Large Open-science Multilingual Language Model, supporting 46 natural languages and 12 programming languages

A large-scale multilingual speech recognition model introduced by Meta AI, featuring 1 billion parameters and supporting character-level transcription for 60 languages

This is a neural machine translation model for translating from Hungarian to English, part of the OPUS-MT project.

A neural machine translation model for translating from Bulgarian to English, developed based on the OPUS-MT project.

This is a neural machine translation model for English to Lithuanian translation, part of the OPUS-MT project.

This is a neural machine translation model from English to East Slavic languages (including Belarusian, Russian, Ukrainian), part of the OPUS-MT project.

This is a large-scale neural machine translation model based on the Transformer architecture, specifically designed for translating English to Finnish. The model is part of the OPUS-MT project, trained using the Marian NMT framework, and provided through Hugging Face's transformers library.

The XLM model is a cross-lingual pretrained model based on text in 17 languages, using the masked language modeling (MLM) objective

The XLM model is a cross-lingual language model pre-trained on Wikipedia texts in 100 languages using masked language modeling objectives.