Deep Learning over the Internet: Training Language Models Collaboratively

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Deep Learning over the Internet: Training Language Models Collaboratively

Deep Learning over the Internet: Training Language Models Collaboratively

“Modern language models often require a significant amount of compute for pretraining, making it impossible to obtain them without access to tens and hundreds of GPUs or TPUs. Though in theory it might be possible to combine the resources of multiple individuals, in practice, such distributed training methods have previously seen limited success because connection speeds over the Internet are way slower than in high-performance GPU supercomputers.

In this blog post, we describe DeDLOC — a new method for collaborative distributed training that can adapt itself to the network and hardware constraints of participants. We show that it can be successfully applied in real-world scenarios by pretraining sahajBERT, a model for the Bengali language, with 40 volunteers. On downstream tasks in Bengali, this model achieves nearly state-of-the-art quality with results comparable to much larger models that used hundreds of high-tier accelerators…”

Source: huggingface.co/blog/collaborative-training

Paper: https://arxiv.org/abs/2106.10207

October 18, 2021
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