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Train Word embeddings from scratch with Nessvec and PyTorch

Hobson and his colleagues try to figure out how to train word embeddings from scratch using the WikiText2 dataset in PyTorch. The WikiText2 dataset contains redacted words, but they were unable to find the "labels" that reveal the words masked with the symbol ``. If you try to use the `Wik...

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Bibliographic Details
Format: eBook
Language:English
Published: [Place of publication not identified] Manning Publications 2022
Edition:[First edition]
Subjects:
Machine Learning / Http://id.loc.gov/authorities/subjects/sh85079324
Natural Language Processing
Machine Learning / Fast
Apprentissage Automatique
Traitement Automatique Des Langues Naturelles
Natural Language Processing (computer Science) / Fast
Machine Learning
Natural Language Processing (computer Science) / Http://id.loc.gov/authorities/subjects/sh88002425
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:Hobson and his colleagues try to figure out how to train word embeddings from scratch using the WikiText2 dataset in PyTorch. The WikiText2 dataset contains redacted words, but they were unable to find the "labels" that reveal the words masked with the symbol ``. If you try to use the `Wikipedia` package to retrieve Wikipedia pages directly, you may hit the `suggest` bug. There are more than 100 unanswered issues on the project, and the maintainer has pushed any changes for many years. The Tangible AI fork on GitLab fixes this search suggestion bug so we could easily crawl Wikipedia. Unfortunately, the Wikipedia-API package is not very useful for searching and crawling Wikipedia to retrieve text
Physical Description:1 video file (41 min.) sound, color

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