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![[논문리뷰] SUPER-NATURALINSTRUCTIONS: Generalization via Declarative Instructions on 1600+ NLP Tasks](https://img1.daumcdn.net/thumb/R750x0/?scode=mtistory2&fname=https%3A%2F%2Fblog.kakaocdn.net%2Fdna%2FbhdRgX%2FbtsFOWpNtqz%2FAAAAAAAAAAAAAAAAAAAAAF5d994hSqV9BNW4Eo9Czq6xbnyF9oXzw9MoU2PTYx_G%2Fimg.png%3Fcredential%3DyqXZFxpELC7KVnFOS48ylbz2pIh7yKj8%26expires%3D1753973999%26allow_ip%3D%26allow_referer%3D%26signature%3DWd2Yrz6qip8MPDHM0cjOkhwBM34%253D)
[논문리뷰] SUPER-NATURALINSTRUCTIONS: Generalization via Declarative Instructions on 1600+ NLP Tasks
https://arxiv.org/abs/2204.07705 Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks How well can NLP models generalize to a variety of unseen tasks when provided with task instructions? To address this question, we first introduce Super-NaturalInstructions, a benchmark of 1,616 diverse NLP tasks and their expert-written instructions. Our arxiv.org Summary 1..
![[HPC Lab] LSTM으로 Google Cluster Trace Data의 CPU rate 예측하기 - 예측](https://img1.daumcdn.net/thumb/R750x0/?scode=mtistory2&fname=https%3A%2F%2Fblog.kakaocdn.net%2Fdna%2Fd224Bj%2FbtsFB8c6bTd%2FAAAAAAAAAAAAAAAAAAAAAJv-3QbKCdLwFLmodUQwr0ggH5unKoplUcxy0J5TtxYq%2Fimg.png%3Fcredential%3DyqXZFxpELC7KVnFOS48ylbz2pIh7yKj8%26expires%3D1753973999%26allow_ip%3D%26allow_referer%3D%26signature%3DWKtRsnJyvEtYMR58odgck2WsWdI%253D)
[HPC Lab] LSTM으로 Google Cluster Trace Data의 CPU rate 예측하기 - 예측
https://welldonecode.tistory.com/96 [HPC Lab] LSTM으로 Google Cluster Trace Data의 CPU rate 예측하기 - 데이터 전처리 Cluster Autometic DR 논문의 공저자를 목표로 대장정을 시작한다. 아래의 google 공식 github에서 cluter trace data 2011 (version 2) 를 이용하여 CPU rate에 관련된 데이터를 만들고자 한다. https://github.com/google/clus welldonecode.tistory.com 이전 포스팅에서 데이터 전처리를 완료하여 단일 클러스터의 CPU, Memory 사용량에 대한 10분 주기의 시계열 데이터를 생성하였다. 이번엔 기본적인 LSTM 모델을 생성하여 해..
![[HPC Lab] LSTM으로 Google Cluster Trace Data의 CPU rate 예측하기 - 데이터 전처리](https://img1.daumcdn.net/thumb/R750x0/?scode=mtistory2&fname=https%3A%2F%2Fblog.kakaocdn.net%2Fdna%2FnrXgs%2FbtsFBMg0rs3%2FAAAAAAAAAAAAAAAAAAAAAOAgy6USw4JgzqwylcXqIG4D_-5h8ExOvIGAEezVnRKc%2Fimg.png%3Fcredential%3DyqXZFxpELC7KVnFOS48ylbz2pIh7yKj8%26expires%3D1753973999%26allow_ip%3D%26allow_referer%3D%26signature%3DVWD04h6BOdSGIh6j9QYeCMxCVNo%253D)
[HPC Lab] LSTM으로 Google Cluster Trace Data의 CPU rate 예측하기 - 데이터 전처리
Cluster Autometic DR 논문의 공저자를 목표로 대장정을 시작한다. 아래의 google 공식 github에서 cluter trace data 2011 (version 2) 를 이용하여 CPU rate에 관련된 데이터를 만들고자 한다. https://github.com/google/cluster-data GitHub - google/cluster-data: Borg cluster traces from Google Borg cluster traces from Google. Contribute to google/cluster-data development by creating an account on GitHub. github.com Alibaba의 데이터셋도 고려하였지만, 데이터셋 크기가 크고 ..