Introducing Muse, your personal AI agent from Meta that gets things done across every part of life.
Download the Muse app and get started: https://t.co/KBjYWfshGo
#PyTorch Distributed Checkpointing now supports @huggingface safetensors—making it easier to save/load checkpoints across ecosystems.
New APIs let you read/write safetensors via fsspec paths. First adopter: torchtune, with a smoother checkpointing flow.
📚 Learn more: https://t.co/AblDWehmZV
#OpenSourceAI #DistributedAI #MLCommunity
We're kicking off a new PyTorch Compiler video series 🎬 In the first episode, Avik Chaudhuri discusses a few simple principles that drive the programming model for export & illustrates them via a series of examples.
🔍 Export creates ahead-of-time IR representations of PyTorch models that provide higher safety and coverage than previous technologies like TorchScript and FX. Exported IR can be further lowered and optimized to run on heterogeneous hardware by runtimes such as ONNX, TensorRT, ExecuTorch, and AOTInductor.
📺 Watch now: https://t.co/xYr1ZFJGnq
Nearly 60 developers joined the PyTorch Hangzhou meetup to share work on vLLM, RL acceleration, AI infra, and more.
📖 Read the full recap: https://t.co/a06bCUymeR
#PyTorch#OpenSourceAI#MachineLearning#AIInfrastructure
PyTorch DCP (Distributed Checkpointing) has recently enabled new optimizations for asynchronous checkpointing in order to reduce the collective overhead and GPU utilization drop and thus improve overall checkpointing efficiency. 🚀Read our latest blog to learn more: https://t.co/Y2rkzqd9eT
#PyTorch #Optimization