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  1. DeepSpeed
    https://www.deepspeed.ai/tutorials/zero

    Zero Redundancy Optimizer - DeepSpeed

    • Zero-One Adam

      Watch out! 1) The NCCL-based implementation requires PyTorch >= 1.8 …

    • ZeRO-Offload

      ZeRO-3 Offload consists of a subset of features in our newly released ZeRO …

    • GAN

      Train your first GAN model with DeepSpeed! Note: In the case where we …

    • Mixture of Experts

      DeepSpeed v0.5 introduces new support for training Mixture of Experts (MoE) …

    • Communication Logging

      For advanced users, the debug option will append the calling function of each …

    • Cifar-10

      CIFAR-10 Tutorial Contents. Running Original CIFAR-10; Enabling …

    • Mixture-of-Quantization

      DeepSpeed introduces new support for model compression using quantization, …

    • PyTorch Profiler

      Profile CPU or GPU activities. The activities parameter passed to the Profiler …

    Afficher uniquement les résultats de deepspeed.ai

  2. Vidéos de Live Messenger ZERO3

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  3. DeepSpeed
    https://www.deepspeed.ai/tutorials/inference-tutorial

    Getting Started with DeepSpeed for Inferencing Transformer ...

  4. YouTube
    https://www.youtube.com/live/8JvF-xsiJGc

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  5. Autres questions posées
    What is zero 3?
    ZeRO-3, the third stage of ZeRO, partitions the full model state (i.e., weights, gradients, and optimizer states) to scale memory savings linearly with the degree of data parallelism. ZeRO-3 can be enabled in the JSON configuration. A full description of these configurations is available here.

    Zero Redundancy Optimizer - DeepSpeed

    deepspeed.ai
    What is zero-3 offload?
    ZeRO-3 Offload consists of a subset of features in our newly released ZeRO-Infinity. Read our ZeRO-Infinity blog to learn more! We recommend that you read the tutorials on Getting Started and ZeRO before stepping through this tutorial.

    ZeRO-Offload - DeepSpeed

    deepspeed.ai
    How does zero-3 work?
    ZeRO-3 will automatically collect and partition them during the forward and backward passes. In addition, ZeRO-3 includes the infinity offload engine to form ZeRO-Infinity ( paper ), which can offload to both CPU and NVMe memory for huge memory savings. We use the DeepSpeed Megatron-LM GPT-2 code for this exercise.

    Zero Redundancy Optimizer - DeepSpeed

    deepspeed.ai
    Can zero-3 be enabled in a JSON configuration?
    ZeRO-3 can be enabled in the JSON configuration. A full description of these configurations is available here. ZeRO-Infinity uses DeepSpeed’s infinity offload engine to offload the full model state to CPU or NVMe memory, allowing for even larger model sizes. Offloading can be enabled inside the DeepSpeed configuration:

    Zero Redundancy Optimizer - DeepSpeed

    deepspeed.ai
    What is the difference between zero-infinity and zero-offload?
    ZeRO-Infinity is able to offload more data than ZeRO-Offload and has more effective bandwidth utilization and overlapping of computation and communication. We make two further changes to model initialization in order to support models that exceed local system memory, but not total system memory.

    Zero Redundancy Optimizer - DeepSpeed

    deepspeed.ai
    How do I enable Zero Stage 1?
    To enable ZeRO stage 1, we simply update the DeepSpeed JSON config file as below: As seen above, we set two fields in the zero_optimization key. Specifically we set the stage field to 1, and the optional reduce_bucket_size for gradient reduction to 500M.

    Zero Redundancy Optimizer - DeepSpeed

    deepspeed.ai
    Commentaires
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  7. Github
    https://github.com/OpenBMB/MiniCPM-V/issues/184

    finetune_lora.sh use ds_config_zero3.json error #184 - GitHub

  8. Kent Online
    https://www.kentonline.co.uk/maidstone/archive/...

    Maidstone News, latest live news from the Kent Messenger

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  10. AP News
    https://apnews.com/article/india-election-2024...

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  11. ニコニコ生放送
    https://live.nicovideo.jp/watch/lv345394788

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