Shenggan/awesome-distributed-ml
A curated list of awesome projects and papers for distributed training or inference
This is a curated collection of resources for machine learning engineers and researchers who are working with extremely large AI models. It brings together open-source projects and research papers that focus on how to efficiently train and deploy these large models using distributed computing. If you're tackling the challenge of building or fine-tuning models that exceed the capacity of a single machine, this list provides tools and techniques to help you scale your efforts effectively.
266 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher designing, training, or deploying large-scale AI models, especially those like large language models or complex neural networks.
Not ideal if you are a data scientist or developer working with smaller models that can be handled on a single GPU or CPU, or if you are not involved in the low-level systems aspects of machine learning.
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Oct 08, 2024
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