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https://github.com/hundredblocks/large-model-parallelism
Functional local implementations of main model parallelism approaches
https://github.com/hundredblocks/large-model-parallelism
Last synced: 3 months ago
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Functional local implementations of main model parallelism approaches
- Host: GitHub
- URL: https://github.com/hundredblocks/large-model-parallelism
- Owner: hundredblocks
- License: gpl-3.0
- Created: 2023-02-21T18:15:17.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-02-21T18:44:13.000Z (over 1 year ago)
- Last Synced: 2024-06-15T11:33:02.317Z (5 months ago)
- Language: Jupyter Notebook
- Size: 823 KB
- Stars: 91
- Watchers: 12
- Forks: 5
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
![large-model-parallelism-illustration](https://user-images.githubusercontent.com/7229234/220430946-4b4ab497-7f86-40af-ac43-3e2793900bce.jpg)
# Model parallelism 101
Learn how model parallelism enables training models like stable diffusion and Chat GPT in less than 300 lines of code. This [notebook](https://github.com/hundredblocks/large-model-parallelism/blob/main/large-model-parallelism.ipynb) provides practical local implementations of the main model parallelism methods. It explores three approaches: data parallelism, tensor parallelism, and pipeline parallelism with a 2-layer MLP example that can be naturally extended to more complex models.
Reading this notebook will give you a solid overview of model parallelism techniques and an intuition for how to implement them.
Pull requests welcome. Illustration above generated with Lexica's Aperture model.