65 citations · 177 across the 4 of their papers we have counts for
4 papers
Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models
Terry Yue Zhuo, Armel Zebaze, Nitchakarn Suppattarachai +4
The high cost of full-parameter fine-tuning (FFT) of Large Language Models (LLMs) has led to a series of parameter-efficient fine-tuning (PEFT) methods. However, it remains unclear…
Zephyr: Direct Distillation of LM Alignment
Lewis Tunstall, Edward Beeching, Nathan Lambert +11
We aim to produce a smaller language model that is aligned to user intent. Previous research has shown that applying distilled supervised fine-tuning (dSFT) on larger models signif…
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,…
SantaCoder: don't reach for the stars!
Loubna Ben Allal, Raymond Li, Denis Kocetkov +38
The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code. This tech report describes the progress of the col…