162 citations · 594 across the 11 of their papers we have counts for
5 papers · 1 filter
Measuring Data
Margaret Mitchell, Alexandra Sasha Luccioni, Nathan Lambert +7
We identify the task of measuring data to quantitatively characterize the composition of machine learning data and datasets. Similar to an object's height, width, and volume, data…
The Stack: 3 TB of permissively licensed source code
Denis Kocetkov, Raymond Li, Loubna Ben Allal +10
Large Language Models (LLMs) play an ever-increasing role in the field of Artificial Intelligence (AI)--not only for natural language processing but also for code understanding and…
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…
SEAL : Interactive Tool for Systematic Error Analysis and Labeling
Nazneen Rajani, Weixin Liang, Lingjiao Chen +2
With the advent of Transformers, large language models (LLMs) have saturated well-known NLP benchmarks and leaderboards with high aggregate performance. However, many times these m…
Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements
Leandro von Werra, Lewis Tunstall, Abhishek Thakur +16
Evaluation is a key part of machine learning (ML), yet there is a lack of support and tooling to enable its informed and systematic practice. We introduce Evaluate and Evaluation o…