8 Advanced parallelization - Deep Learning with JAX

Por um escritor misterioso

Descrição

Using easy-to-revise parallelism with xmap() · Compiling and automatically partitioning functions with pjit() · Using tensor sharding to achieve parallelization with XLA · Running code in multi-host configurations
8 Advanced parallelization - Deep Learning with JAX
Build a Transformer in JAX from scratch
8 Advanced parallelization - Deep Learning with JAX
Efficiently Scale LLM Training Across a Large GPU Cluster with
8 Advanced parallelization - Deep Learning with JAX
Intro to JAX for Machine Learning, by Khang Pham
8 Advanced parallelization - Deep Learning with JAX
Lecture 2: Development Infrastructure & Tooling - The Full Stack
8 Advanced parallelization - Deep Learning with JAX
Why You Should (or Shouldn't) be Using Google's JAX in 2023
8 Advanced parallelization - Deep Learning with JAX
Using Cloud TPU Multislice to scale AI workloads
8 Advanced parallelization - Deep Learning with JAX
Differentiable sampling of molecular geometries with uncertainty
8 Advanced parallelization - Deep Learning with JAX
Why You Should (or Shouldn't) be Using Google's JAX in 2023
8 Advanced parallelization - Deep Learning with JAX
Lecture 2: Development Infrastructure & Tooling - The Full Stack
8 Advanced parallelization - Deep Learning with JAX
7 Parallelizing your computations - Deep Learning with JAX
8 Advanced parallelization - Deep Learning with JAX
What is Google JAX? Everything You Need to Know - Geekflare
8 Advanced parallelization - Deep Learning with JAX
The State of Machine Learning Frameworks in 2019
de por adulto (o preço varia de acordo com o tamanho do grupo)