# Masked Language Model

A modern Russian version of a unidirectional and bidirectional encoder Transformer model, pre-trained on approximately 2 trillion tokens of Russian, English, and code data, with a context length of up to 8,192 tokens.

A monolingual Slovak BERT model released by the HPLT project, trained on the LTG-BERT architecture, suitable for masked language modeling tasks

MizBERT is a masked language model (MLM) pre-trained on Mizo text corpora, utilizing the BERT architecture to effectively learn contextual representations of Mizo vocabulary.

ESM-2 is a state-of-the-art protein model trained on masked language modeling objectives, suitable for protein sequence analysis and prediction tasks

A masked language model fine-tuned on MacBERT for Chinese typo correction

A BERT-based masked language model for Buddhist Sanskrit text processing, specifically designed for handling Buddhist Sanskrit texts

A BERT-like masked language model for Turkish, operating at the character level, pre-trained using SpanBERT-style character span masking.

This is a version of Tohoku University's BERT Large Japanese model converted for use in Rust

TAPAS (Table Parser) is a table-based pre-trained language model developed by Google Research, specifically designed for processing tabular data and natural language queries.

TAPAS is a pre-trained language model based on tabular data, specifically designed for natural language tasks related to tables.

KoBERT-LM is a pre-trained language model optimized for Korean, based on the BERT architecture and further pre-trained specifically for Korean text.

A variant of the BERT model pre-trained using knowledge distillation technology, with a hidden layer dimension of 240 and 12 attention heads, suitable for masked language modeling tasks.

Bangla BERT Base is a pre-trained Bengali language model based on the BERT architecture, supporting various downstream NLP tasks.

TAPAS is a table-based pre-trained language model specifically designed for processing tabular data and related queries.

Indonesian masked language model based on RoBERTa architecture, trained on the OSCAR corpus with a validation accuracy of 62.45%