Webinar
The BigScience Project: Collaboratively training a large multilingual language model
Recent breakthroughs in Natural Language Processing (NLP) demonstrate the ability of Large Language Models - LLM (such as GPT-3 and T5) to solve diverse problems. However, building such large models raises challenges on data, training, and deployment considerations. Recently, the Big Science collaborative initiative - a group of over 1,000 researchers from academia and industry - developed BLOOM, an open source massive 176 billion parameter multilingual model.
In this webinar, we will present the key learnings of the BigScience initiative in developing the BLOOM language model in a transparent and collaborative way. This is an opportunity to discover what motivated the creation of the workshop, and the 4 month training process on the Jean Zay (IDRIS) supercomputer* using 384 NVIDIA A100 GPUs, and discuss the BLOOM achievements.
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Lucile Saulnier is a Machine Learning engineer at Hugging Face. She develops and supports the use of open source tools. She is also actively involved in research projects in the field of Deep Learning such as BigScience - a one-year collaborative project aiming to produce a large multilingual language model and a very large multilingual text dataset on the Jean Zay supercomputer.
Meriem is a senior Deep Learning data scientist at NVIDIA, supporting partners delivering AI/deep learning solutions. Meriem area of expertise is conversational AI and large scale Natural Language Processing. Meriem holds a Ph.D. in signal and image from Telecom ParisTech, where she studied machine learning applied to audio-visual content.
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Date & Time: Wednesday, April 22, 2018