foundation-model-stack/fms-model-optimizer
FMS Model Optimizer is a framework for developing reduced precision neural network models.
This tool helps AI practitioners optimize large neural network models like those used in vision, speech, or natural language processing. It takes your existing PyTorch deep learning models and applies advanced techniques to reduce their size and computational requirements. The output is a more efficient, "reduced precision" model that runs faster and uses less memory, ideal for deployment in resource-constrained environments. AI/ML engineers or researchers who need to deploy models more efficiently would use this.
Used by 1 other package. Available on PyPI.
Use this if you need to make your large neural network models (especially LLMs) smaller and faster for deployment without significantly losing accuracy.
Not ideal if you are working with small models that don't require significant optimization or if you are not familiar with deep learning model quantization techniques.
Stars
21
Forks
18
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 23, 2026
Commits (30d)
0
Dependencies
9
Reverse dependents
1
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