Training or fine-tuning Large Language Models (LLMs) involves dealing with incredibly large models and datasets. These models can have billions of parameters and require vast amounts of GPU memory to ...

This Python script is provided "as is" to the open-source community to contribute to human advancement and collaborative research in deep learning. It offers a scalable solution for distributed ...

In the context of deep learning model training, checkpoint-based error recovery techniques are a simple and effective form of fault tolerance. By regularly saving the ...

AI startup Prime Intellect trained Intellect-1, a 10-billion-parameter language model, in just eleven days using a decentralized approach. It plans to open source it within a week. The company used ...

Poor utilization is not the single domain of on-prem datacenters. Despite packing instances full of users, the largest cloud providers have similar problems. However, just as the world learned by ...

Abstract: With the continuous advancement of large-scale models and expanding volumes of data, a single acceleration hardware is no longer sufficient to meet the training demands. Simply stacking ...