網際網路上的深度學習：以協作方式訓練語言模型
Original: Deep Learning over the Internet: Training Language Models Collaboratively
In the field of artificial intelligence, training large language models (LLMs) has always been an extremely resource-intensive task…
本文介紹 Hugging Face 如何利用去中心化深度學習庫 `hivemind`，在網際網路上進行協作式模型訓練。透過分散式雜湊表（DHT）與容錯演算法，全球志願者能用自己的 GPU 共同訓練出孟加拉語模型 SahajBERT。這種方法打破了大型科技公司對大模型算力的壟斷，為開源社群提供了一條去中心化訓練的新路徑。
In the field of artificial intelligence, training large language models (LLMs) has always been an extremely resource-intensive task. Traditionally, this requires hundreds of high-performance GPUs performing synchronized training in dedicated data centers equipped with high-speed networks (such as InfiniBand). This prohibitively high barrier has long allowed large-scale model development to be monopolized by a handful of tech giants.
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