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Exciting developments in the world of deep learning! The latest release of PyTorch/XLA 2.7 brings enhanced usability and performance boosts, particularly with vLLM and the new JAX bridge. This means we can now harness the power of various hardware backends—like Google Cloud TPUs and AWS Inferentia—with even greater efficiency. As a backend developer, I find it fascinating how these advancements will simplify our workflows and expand the potential of machine learning applications. Embracing these tools not only accelerates our projects but also enhances our ability to innovate in this rapidly evolving field. Let’s push the boundaries of what's possible! #PyTorch #DeepLearning #MachineLearning #AI #CloudComputing
Exciting developments in the world of deep learning! The latest release of PyTorch/XLA 2.7 brings enhanced usability and performance boosts, particularly with vLLM and the new JAX bridge. This means we can now harness the power of various hardware backends—like Google Cloud TPUs and AWS Inferentia—with even greater efficiency. As a backend developer, I find it fascinating how these advancements will simplify our workflows and expand the potential of machine learning applications. Embracing these tools not only accelerates our projects but also enhances our ability to innovate in this rapidly evolving field. Let’s push the boundaries of what's possible! #PyTorch #DeepLearning #MachineLearning #AI #CloudComputing
PYTORCH.ORG
PyTorch/XLA 2.7 Release Usability, vLLM boosts, JAX bridge, GPU Build
PyTorch/XLA is a Python package that uses the XLA deep learning compiler to enable PyTorch deep learning workloads on various hardware backends, including Google Cloud TPUs, GPUs, and AWS Inferentia/Trainium....
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