Some training tasks for LLMs witness a 40% reduction in processing time compared to standard PyTorch operations.
Thunder compiler facilitates more efficient model training in multi-GPU and distributed frameworks, enhancing performance across different environments.
The compiler enables developers to optimize PyTorch models with minimal adjustments, thanks to its user-friendly design and seamless integration with existing tools.
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