NLP – PyTorch

Case Studies

The Why and How of Scaling Large Language Models

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and…

PyTorch FoundationJanuary 4, 2022

Case Studies

Using a Grapheme to Phoneme Model in Cisco’s Webex Assistant

Grapheme to Phoneme (G2P) is a function that generates pronunciations (phonemes) for words based on…

PyTorch FoundationSeptember 7, 2021

Case Studies

University of Pécs enables text and speech processing in Hungarian, builds the BERT-large model with just 1,000 euro with Azure

Everyone prefers to use their mother tongue when communicating with chat agents and other automated…

PyTorch FoundationAugust 10, 2021

Case Studies

AI21 Labs Trains 178-Billion-Parameter Language Model Using Amazon EC2 P4d Instances, PyTorch

AI21 Labs uses machine learning to develop language models focused on understanding meaning, and in…

PyTorch FoundationJune 7, 2021

Case Studies

Deepset achieves a 3.9x speedup and 12.8x cost reduction for training NLP models by working with AWS and NVIDIA

At deepset, we’re building the next-level search engine for business documents. Our core product, Haystack,…

PyTorch FoundationJanuary 27, 2021

Case Studies

PyTorch at Dolby Labs

Hear how Dolby Labs is using PyTorch to develop deep learning for audio, and learn…

PyTorch FoundationNovember 6, 2019

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