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Why Zephon? The data that a model sees during training is one of the most powerful levers we have for influencing how well it performs. Much of the day to day work... The post Bringing Elastically Deterministic Data Loading to TorchTitan with Zephon appeared first on PyTorch .
Today, Meta is releasing the weights for Muse Spark Open, the most capable US open weights model to date. It’s available today on Hugging Face under the Muse Model License. Muse... The post Muse Spark 1.2 Is Now Open Weights appeared first on PyTorch .
TL;DR Deploying PyTorch models on microcontrollers has historically required converting to other framework formats, maintaining separate toolchains, and debugging cross framework numerical mismatches. ExecuTorch eliminates this conversion step entirely. The Cortex M... The post Bringing ExecuTorch to Arm Cortex M…
TL;DR The PyTorch based software stack for IBM’s Spyre accelerator recently moved its torch.compile backend from sendnn, a separate compilation stack built entirely from scratch, to backend=inductor, an open source backend built... The post Extending Inductor for the IBM Spyre Accelerator appeared first on PyTorch .
TL;DR Agentic workloads change the traffic an inference server sees. Unlike single turn chat, an agent session can involve a large initial prefill, repeated model calls, and subagents running in parallel,... The post Session Aware Agentic Inference with NVIDIA Dynamo appeared first on PyTorch .
TL;DR Spyre becomes a native PyTorch device by connecting PyTorch’s existing device, allocator, stream, and compiler abstractions through torch spyre to the Spyre runtime and firmware. PrivateUse1 gives Spyre a real... The post Building Spyre as a Native PyTorch Device appeared first on PyTorch .
This post explores the FBTriton kernel design for Table Batched Embedding (TBE) forward and backward passes. These core operators handle embedding lookups across thousands of sharded GPUs within recommendation systems.... The post Modernizing Table Batched Embeddings with FBTriton appeared first on PyTorch .
TL;DR If you need to decode or encode media, whether it’s images, video, or audio, use TorchCodec. If you need to transform media, use TorchVision for images and video, and... The post Evolution of the PyTorch Media Processing Landscape appeared first on PyTorch .
TL;DR The Accelerator Integration Working Group plays a vital role in standardizing how new hardware architectures connect to the open source AI ecosystem. As compute platforms diversify across cloud, edge,... The post PyTorch Hardware Enablement: Updates from the Accelerator Integration Working Group appeared first…
We’re excited to bring you the new PyTorch Certified Associate (PTCA) Certification Pathway, combining focused learning modules and the PyTorch Certified Associate (PTCA) certification exam together in one structured experience... The post New Pathway to PyTorch Certified Associate (PTCA) Certification appeared first…
TL;DR In this blog post, we present our work on Jagged Flash Attention (JFA) — the attention kernel behind Meta’s Generative Ads Model (GEM) — on NVIDIA Blackwell (B200), built... The post Optimizing Jagged Flash Attention with TLX: The Road Toward SOTA FA4 on Blackwell appeared first on PyTorch .
