22 datasets found

The dataset is used for training and testing the proposed punctuation restoration and inverse text normalization models.

A large language model that is significantly larger than the largest model tested in the results discussed above.

The dataset used in the paper is not explicitly mentioned, but it is mentioned that the authors trained a 16 layers transformer (Vaswani et al., 2017) based language model on...

The dataset used in the paper is the Stanford Sentiment Treebank (SST) dataset, which contains standard train/dev/test sets and two subtasks: binary sentence classification or...

The Pile dataset contains 3.5 million samples of diverse text for language modeling.

The dataset used in the paper is LLaMA, a large language model.

The FastText dataset is a subword token embedding model. It produces a vector representation of a word based on composing embeddings of the character n-grams composing the word.

The LibriSpeech LM corpus used for pre-training speech-text models.

Morfessor 2.0 dataset for English, Finnish and Turkish language models

Den samiske tekstbanken dataset for North S´ami language model

Morpho Challenge 2010 dataset for English, Finnish and Turkish language models

The dataset used for pre-training language models, containing a large collection of text documents.

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.

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

The Wiki-Auto dataset is a text simplification dataset.

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 dataset used in this paper is the WikiText-103 dataset, which contains a large corpus of text.

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...