# [Next Steps](https://learn.arm.com/learning-paths/servers-and-cloud-computing/torchbench/_next-steps/)

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/servers-and-cloud-computing/torchbench/)
- [Measure and accelerate the inference performance of PyTorch models on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/torchbench/pytorch-benchmark/)
- [Next Steps](https://learn.arm.com/learning-paths/servers-and-cloud-computing/torchbench/_next-steps/)

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## Continue Learning
### Read related resources
Find more information about the topics in this Learning Path:
- [PyTorch Benchmarks](https://github.com/pytorch/benchmark)
- [PyTorch Inference Performance Tuning on AWS Graviton Processors](https://pytorch.org/tutorials/recipes/inference_tuning_on_aws_graviton.html)
- [ML inference on Graviton CPUs with PyTorch](https://github.com/aws/aws-graviton-getting-started/blob/main/machinelearning/pytorch.md)
- [PyTorch Documentation](https://pytorch.org/docs/stable/index.html)

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