揭秘 BLOOM 訓練背後的技術：如何用 Megatron-DeepSpeed 訓練 1760 億參數開源大模型
Original: The Technology Behind BLOOM Training
This article documents in detail how the BigScience project trained BLOOM, an open-source multilingual large language model with 176…
Hugging Face 詳細公開了 1760 億參數開源模型 BLOOM 的訓練技術細節。該模型在法國 Jean Zay 超級電腦上，利用 384 張 NVIDIA A100 80GB GPU 進行了為期 117 天的訓練。核心技術採用 Megatron-DeepSpeed 框架，結合了張量並行、流水線並行與數據並行的「3D 並行」方案，並透過 BF16 精度解決了大規模訓練中的數值不穩定問題。
This article documents in detail how the BigScience project trained BLOOM, an open-source multilingual large language model with 176 billion parameters. This was an enormously challenging engineering feat, as the 176B model size (approximately 352 GB of 16-bit weights) far exceeded the memory capacity of any single GPU.
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