siboehm/ShallowSpeed
Small scale distributed training of sequential deep learning models, built on Numpy and MPI.
This project helps machine learning engineers efficiently train deep learning models that process data sequentially, like multilayer perceptrons. You provide your dataset and model architecture, and it outputs a trained model faster by distributing the workload. It's designed for developers building and optimizing these types of models.
163 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer working with sequential deep learning models and need to accelerate training across multiple computing resources.
Not ideal if you are working with complex, non-sequential model architectures or require a production-ready, highly optimized distributed training framework.
Stars
163
Forks
9
Language
Python
License
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Category
Last pushed
Oct 19, 2023
Commits (30d)
0
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