# Large-scale corpus

XLMR-MaCoCu-tr is a language model pretrained on large-scale Turkish text, part of the MaCoCu project, trained using 35GB of Turkish text.

This model is a Wav2Vec2 base model pre-trained on 3,000 hours of Vietnamese speech data, suitable for Vietnamese speech recognition tasks, and requires fine-tuning on downstream tasks for use.

FERNET-C5 is a Czech monolingual BERT base model pretrained on a 93GB large-scale cleaned Czech web corpus (C5).

Large-scale speech pre-training model trained on the Spanish subset of the VoxPopuli corpus, suitable for Spanish speech recognition tasks

XLM-RoBERTa is an extended version of a cross-lingual sentence encoder, trained on 2.5T of data across 100 languages, achieving excellent performance in multiple cross-lingual benchmarks.

mGPT is a multilingual generation model pretrained on the mC4 dataset, supporting 101 languages, using a Transformer architecture similar to GPT-2.

mT5 is a multilingual variant of the T5 model, pretrained on the mC4 corpus covering 101 languages, suitable for multilingual text processing tasks.

RoBERTa base model trained on large-scale Ukrainian corpus, suitable for Ukrainian natural language processing tasks

Large wav2vec2 model trained on 2.9K hours of French speech, supporting spontaneous speech, read speech, and broadcast speech processing

Base wav2vec2 model trained on 2.6K hours of French speech data, excluding spontaneous speech