alibabacloud-pai-dlc-jobAlibaba Cloud PAI-DLC (Deep Learning Containers) job management skill. Covers: distributed training job CRUD, monitoring (logs and events), and GPU sanity check. Triggers: "DLC", "PAI-DLC", "create-job", "list-jobs", "get-job", "stop-job", "update-job", "get-pod-logs", "get-job-events", "get-pod-events", "list-job-sanity-check-results".
Install via ClawdBot CLI:
clawdbot install sdk-team/alibabacloud-pai-dlc-jobGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses system directories or attempts privilege escalation
sudo mvCalls external URL not in known-safe list
https://ram.console.aliyun.com/manage/akAudited May 22, 2026 · audit v1.0
Generated Oct 4, 2026
AI研发团队使用PAI-DLC创建TensorFlow或PyTorch分布式训练作业,利用ECS按量付费或灵骏专属配额进行大规模模型训练。通过get-pod-logs和get-job-events实时监控训练进度,快速定位收敛问题。
运维人员定期调用list-job-sanity-check-results对GPU等计算设备进行健康检查,提前发现硬件故障风险。结合get-pod-events排查节点异常,保障训练任务稳定性。
算法工程师通过create-job、update-job、stop-job等命令快速迭代实验配置,调整超参数和资源规格。利用list-jobs查看历史作业对比实验结果,提升算法研发效率。
企业搭建基于PAI Workspace的AI平台,通过DLC Job管理不同部门提交的训练任务,结合AIWorkSpace目录管理镜像、数据集和配额。实现资源隔离与统一调度。
团队在微调大语言模型前,通过DLC作业进行小规模训练验证和GPU性能测试。使用sanity check确认算力环境正常后再启动正式训练,降低资源浪费。
用户按实际使用的GPU/CPU资源和训练时长付费,支持ECS按量付费和灵骏专属配额两种模式。平台方通过资源调度效率提升利润率。
将PAI-DLC封装为AI训练平台提供给企业客户,按席位或算力配额订阅收费。提供作业管理、监控、日志分析等增值功能。
基于DLC训练能力提供模型微调托管服务,客户提交数据即可获得定制化模型。整合训练、监控、部署全链路。
💬 Integration Tip
务必先完成aliyun CLI版本校验和凭据配置,并为每个API调用生成唯一session-id注入--user-agent以保障可观测性;对stop-job等高危操作需用户确认并显式提高超时重试参数。
Scored Aug 20, 2026
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