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Beginner's Guide to Profiling in PyTorch
Hugging Face Bloghigh confidence
Why it matters
- →Provides a beginner-friendly introduction to profiling in PyTorch, a crucial skill for optimization.
- →Helps developers understand and identify performance bottlenecks in neural networks.
- →Aims to make profiling more accessible, encouraging better optimization practices in AI development.
Hugging Face has introduced a new series focused on profiling in PyTorch, beginning with a guide for beginners on using torch.profiler. The initial post explains how to profile a basic matrix multiplication and addition operation, offering insights into reading profiler traces and understanding the interaction between CPU and GPU. The series aims to help developers optimize their PyTorch code by gradually increasing complexity, eventually covering large language models. This educational effort is designed to make profiling more accessible and useful for developers seeking to improve neural network performance.
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- 1vLLM Boosts Transformers Backend for Native-Speed Inference
Hugging Face Blog · July 8, 2026 · Related
- 2Profiling PyTorch Attention: Insights and Optimizations
Hugging Face Blog · July 10, 2026 · Same story
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