65 citations · 117 across the 5 of their papers we have counts for
6 papers
CIDAR: Culturally Relevant Instruction Dataset For Arabic
Zaid Alyafeai, Khalid Almubarak, Ahmed Ashraf +9
Instruction tuning has emerged as a prominent methodology for teaching Large Language Models (LLMs) to follow instructions. However, current instruction datasets predominantly cate…
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Hugo Laurençon, Lucile Saulnier, Thomas Wang +51
As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop,…
BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting
Zheng-Xin Yong, Hailey Schoelkopf, Niklas Muennighoff +12
The BLOOM model is a large publicly available multilingual language model, but its pretraining was limited to 46 languages. To extend the benefits of BLOOM to other languages witho…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Crosslingual Generalization through Multitask Finetuning
Niklas Muennighoff, Thomas Wang, Lintang Sutawika +16
Multitask prompted finetuning (MTF) has been shown to help large language models generalize to new tasks in a zero-shot setting, but so far explorations of MTF have focused on Engl…
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts
Stephen H. Bach, Victor Sanh, Zheng-Xin Yong +24
PromptSource is a system for creating, sharing, and using natural language prompts. Prompts are functions that map an example from a dataset to a natural language input and target…