52 datasets found

A dataset for language modeling, where the goal is to predict the next word in a sequence given the previous words.

A dataset for language modeling, where the goal is to predict the next word in a sequence given the previous words.

The Penn Treebank dataset is used for sentence-level language modeling, and the 90 million word subset of Wikipedia is used for paraphrasing.

The Chinese Poetry dataset is a dataset of Chinese poems used for language modeling.

Word2Vec is a distributed word embedding generator that uses an artificial neural network to learn dense vector representations of words.

The Penn Treebank dataset contains one million words of 1989 Wall Street Journal material annotated in Treebank II style, with 42k sentences of varying lengths.

The dataset used in this paper is Wikitext-103, a general English language corpus containing good and featured Wikipedia articles.

The OSCAR 22.01 corpus is a document-oriented corpus that is used for pre-training large generative language models. It is a multilingual corpus that contains documents holding...

The OSCAR corpus is a multilingual web corpus that is used for pre-training large generative language models. It is a document-oriented corpus that is comparable in size and...

The Common Crawl (CC) project browses and indexes all content available online. It generates 200-300 TiB of data per month (around 5% of which is in French), and constitutes the...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors tested the proposed method on three real data sets for the most relevant security...

The Penn Treebank (PTB) dataset is used for word ordering task. The dataset is used to evaluate the performance of different models for word ordering.