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For questions related to the transformer, which is a deep machine learning model introduced in 2017 in the paper "Attention Is All You Need", used primarily in the field of natural language processing (NLP).
6
votes
How do open source LLMs compare to GPT-4?
The remarkable performance of GPT 4 is due to the massive size of its architecture and the amount of data it was trained on, which costs a lot of money. Few organizations have the hardware resources a …
1
vote
Accepted
How to construct Transformers to predict multidimensional time series?
There is an implementation of the paper ("Adversarial Sparse Transformer for Time Series Forecasting"), in Python using Pytorch, here. … UPDATE
There is also a paper, "Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting", by Zhou et al., which does forecasts on univariate and multivariate data. …
5
votes
What kind of word embedding is used in the original transformer?
No, neither Word2Vec nor GloVe is used as Transformers are a newer class of algorithms. Word2Vec and GloVe are based on static word embeddings while Transformers are based on dynamic word embeddings. …