Updated on 2025-08-15 GMT+08:00
Using Lite Cluster Resources
- Using Snt9B for Distributed Training in a Lite Cluster Resource Pool
- Performing PyTorch NPU Distributed Training In a ModelArts Lite Resource Pool Using Ranktable-based Route Planning
- Using Snt9B for Inference in a Lite Cluster Resource Pool
- Using Ascend FaultDiag to Diagnose Logs in the ModelArts Lite Cluster Resource Pool
- Mounting an SFS Turbo File System to a Lite Cluster
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