ShishirPatil/poet
ML model training for edge devices
This tool helps machine learning engineers and researchers train large, complex AI models directly on small, limited-memory devices like smartphones, wearables, and IoT sensors. You input the specifics of your neural network model and your edge device's memory and runtime constraints. It then outputs an optimized training schedule that ensures your model can learn efficiently within those tight limitations.
168 stars. No commits in the last 6 months.
Use this if you need to train a state-of-the-art machine learning model on an edge device with limited RAM, ensuring optimal energy use and performance.
Not ideal if you are training models on cloud GPUs or powerful servers where memory constraints are not a primary concern.
Stars
168
Forks
19
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 29, 2023
Commits (30d)
0
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