kyegomez/Sophia
Effortless plugin and play Optimizer to cut model training costs by 50%. New optimizer that is 2x faster than Adam on LLMs.
This project offers an optimized training method for large language models, allowing machine learning engineers to reduce the computational resources needed. It takes your existing model training setup and, by simply integrating this optimizer, outputs a trained model faster and at half the cost compared to standard methods like Adam. This is designed for AI/ML engineers and researchers working on large-scale model development and pre-training.
381 stars. No commits in the last 6 months.
Use this if you are training large language models and want to significantly cut down on compute costs, training time, and energy consumption without changing your model architecture or infrastructure.
Not ideal if you are working with small models or non-language model tasks, as the primary benefit is seen in the demanding computational environment of LLM pre-training.
Stars
381
Forks
26
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 04, 2024
Commits (30d)
0
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