Webinars

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Webinars

Explore our library of on-demand webinars featuring PyTorch maintainers, contributors, and industry experts. These sessions cover core updates, project deep dives, and practical insights across the PyTorch ecosystem.

PyTorch 2.7 Release Live Q&A

Using PyTorch and DINOv2 for Multi-label Plant Species Classification

PyTorch Expert Exchange – Multi-Modal Tabular Deep Learning with PyTorch Frame

PyTorch 2.6 Release Live Q&A

PyTorch Expert Exchange Hacker Cup AI

How does batching work on modern GPUs?

PyTorch 2.5 Live Q&A

DistServe: disaggregating prefill and decoding for goodput-optimized LLM inference

Efficient Streaming Language Models with Attention Sinks

Using PyTorch for Monocular Depth Estimation Webinar

PyTorch Expert Exchange: Adapting open source models with Open-Instruct and Tulu

PyTorch Expert Exchange: Efficient Generative Models: From Sparse to Distributed Inference

Accelerating LLM family of models on Arm Neoverse based Graviton AWS processors with KleidiAI

torch.compile: The Missing Manual

PyTorch 2.4: Live Q&A

PyTorch Korea User Group: The Beginning, Present, and Future – Junghwan Park

What’s New for PyTorch Developer Infrastructure – Eli Uriegas & Omkar Salpekar

PyTorch 2.0 Q&A: TorchMultiModal

PyTorch 2.0 Q&A: TorchRL

PyTorch 2.0 Q&A: Dynamic Shapes and Calculating Maximum Batch Size

PyTorch 2.0 Q&A: Optimizing Transformers for Inference

PyTorch 2.0 Q&A: Rethinking Data Loading with TorchData

PyTorch 2.0 Ask the Engineers Q&A Series: Deep Dive into TorchInductor and PT2 Backend Integration

PyTorch 2.0 Ask the Engineers Q&A Series: PT2 and Distributed (DDP/FSDP)

PyTorch 2.0 Live Q&A Series: TorchRec and FSDP in Production

PyTorch 2.0 Live Q&A Series: PyTorch 2.0 Export

PyTorch 2.0 Live Q&A Series: A Deep Dive on TorchDynamo

PyTorch 2.0 Live Q&A Series: PT2 Profiling and Debugging

PyTorch 2.0 Q&A Series: How and why you should contribute to tutorials and code to PyTorch

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