16 datasets found

Two simple semantic boundary-based techniques to improve the generalization of language model-based text-to-SQL

The Pile dataset is a large-scale dataset containing 800GB of text data.

The LM-Extraction benchmark is derived from The Pile (Gao et al., 2020) dataset, which contains 15,000 pairs of prefixes and suffixes derived from The Pile dataset (Gao et al.,...

A large language model that can speak and listen.

A platform for aligning a language model with public input.

The dataset used in the paper is Ultrafeedback, which is a preference dataset that contains 63k preference pairs sampled from models other than the SFT model.

The dataset used in the paper is a subset of the Wikipedia corpus, consisting of 7500 English Wikipedia articles belonging to one of the following categories: People, Cities,...

A dataset of 2,857 books written by 141 authors, used for pre-training and fine-tuning a language model for author-stylized text generation.

A general language assistant for aligning language models with human users

The dataset used in the paper for negative augmentation with language model for reading comprehension of abstract meaning

The BigBench dataset is a collection of 12 challenging language model reasoning tasks.

A language model that demonstrates capabilities in processing and generating human-like text.

The dataset is used for training a language model to follow behavioral principles without the use of preference labels, demonstrations, or human oversight.

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

The AlpacaFarm dataset is a large-scale dataset for preference optimization, which consists of a set of instructions and their corresponding responses.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...