TensorFlow 2.1, released last week, allows for mixed-precision training, making use of the Tensor Cores available in the most recent NVidia GPUs. In this post, we report first experimental results and provide some background on what this is all about.
Today, we are delighted to announce PyTorch/XLA SPMD: the integration of GSPMD into PyTorch with an easy to use API. PyTorch developers seeking superior performance and scale can train and serve the largest neural networks while maximizing utilization of AI accelerators, such as Google Cloud TPUs.
This article discusses GPT-2 and BERT models, as well using knowledge distillation to create highly accurate models with fewer parameters than their teachers
In this episode of Open Source Directions we were joined by Jeff Bezanson and Katie Hyatt who talk about the work they have been doing with Julia. Julia is a programming language that was designed from the beginning for high performance. It programs compile to native code for multiple platforms via LLVM. Julia is dynamically typed, feels like a scripting language, and has good support for interactive use.
We were joined by Joris Van den Bossche talked about the work being done with Pandas. Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
Table of Contents Getting Started with Docker for Machine Learning Overview: Why the Need? What Are Containers? How Do Containers Differ from Virtual Machines? Most Popular Container Images TensorFlow PyTorch Python NGINX Install Docker Install Docker Manually Install Docker Desktop…
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