Comments (2)
个人用户可以使用我们提供的镜像跑一些单机实验,资源丰富一点的个人用户也可以跑一些小规模的分布式实验,当然,也欢迎感兴趣的个人用户进行代码的二次开发,自己尝试编译XDL。企业用户可以多关注一下XDL的分布式提交方式,在集群部署和环境准备都完成后,体验XDL在超大规模样本和超大并发下极致性能。
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XDL遵守Apache 2.0协议,个人或企业用户可以在该协议允许的范围内使用XDL。有志于获得XDL企业级支持计划的公司或团队,可以联系[email protected]。
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Related Issues (20)
- 训练时报错
- TDM中叶子结点的embdding是怎么来的
- insufficient processing units
- invalid batch
- TDM serving编译时报错
- AUC bug report
- TDM3.0 beam search采样不会很耗时吗 HOT 3
- 话说现在用TensorFlow分布式训练CTR模型的思路是? HOT 1
- 如何在标准文本数据格式中表示sparse feature的 segments HOT 1
- xdl有没有各个函数功能的详细文档 HOT 1
- build_final_net return a tuple but use as list
- pip install xdl
- help!!! Illegal instruction (core dumped)
- tdm 单机预测评估时卡住没反应 HOT 2
- SyncHook 没有在 worker 之间形成同步?
- ZfsKv是做什么用的?
- mac M2 芯片的可以安装xdl吗? HOT 1
- TDM 的train.py执行异常, item_emb 为空
- Docker Image Format v1 is disabled by default // Docker映像文件版本过低需要升级
- 怎么打开XDL_LOG(DEBUG) 这种日志? HOT 2
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