Finetuning LLMs on a Single GPU Using Gradient Accumulation

Previously, I shared an article using multi-GPU training strategies to speed up the finetuning of large language models. Several of these strategies include mechanisms such as model or tensor sharding that distributes the model weights and computations across different devices to work around GPU memory limitations. However, many of us don’t have access to multi-GPU... Read more »

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