Search Results for author:
Found 8 papers, 4 papers with code
PaLM 2 Technical Report
Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more efficient inference compared to PaLM.
PaLM: Scaling Language Modeling with Pathways
To further our understanding of the impact of scale on few-shot learning, we trained a 540-billion parameter, densely activated, Transformer language model, which we call Pathways Language Model PaLM.
Ranked #1 on
Common Sense Reasoning
on BIG-bench (Known Unknowns)
Scaling Up Models and Data with $\texttt{t5x}$ and $\texttt{seqio}$
Recent neural network-based language models have benefited greatly from scaling up the size of training datasets and the number of parameters in the models themselves.
Pathways: Asynchronous Distributed Dataflow for ML
We present the design of a new large scale orchestration layer for accelerators.
Swift for TensorFlow: A portable, flexible platform for deep learning
Swift for TensorFlow is a deep learning platform that scales from mobile devices to clusters of hardware accelerators in data centers.
Tensors Fitting Perfectly
Multidimensional arrays (NDArrays) are a central abstraction in modern scientific computing environments.
LazyTensor: combining eager execution with domain-specific compilers
Domain-specific optimizing compilers have demonstrated significant performance and portability benefits, but require programs to be represented in their specialized IRs.
OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
