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Geeps: Scalable deep learning on distributed gpus with a gpu-specialized parameter server. Scaling distributed machine learning with the parameter server. Language models are unsupervised multitask learners. Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters. Alpa: Automating inter-and intra-operator parallelism for distributed deep learning. Do the main claims made in the abstract and introduction accurately reflect the paper's If you ran experiments... (a) Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [Y es] Codes and how Did you specify all the training details (e.g., data splits, hyperparameters, how they Did you report error bars (e.g., with respect to the random seed after running experiments multiple times)?