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qualcomm / aimet

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

Why this job: works in the areas we cover, but does not say which job it does

What it does

  • *Spatial SVD*. Tensor decomposition technique to split a large layer into two smaller ones
  • *Channel Pruning*. Removes redundant input channels from a layer and reconstructs layer weights
  • *Per-layer compression-ratio selection*. Automatically selects how much to compress each layer in the model
  • *Weight ranges*. Inspect visually if a model is a candidate for applying the Cross Layer Equalization technique. And the effect after applying the technique
  • *Per-layer compression sensitivity*. Visually get feedback about the sensitivity of any given layer in the model to compression

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit today
Stars
2,747
+4 this week
Licence
Custom
Read before business use
Downloads for
2 systems
Mac, Linux
Latest version
2.43.0
Released 13 days ago
Built with
Python
96% of the code

Is it looked after?

Contributors
12
Last 90 days
Issues
98% closed
30 still open
Pull requests
2,348 merged
10 waiting
Releases
84
28 in the last year

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More: download files, languages, topics and project record

Download files, 2.43.0

  • Mac1 file, 7 downloads
  • Linux1 file, 15 downloads

All files on GitHub (opens in new tab)

Languages

  • Python 96%
  • C++ 3%
  • CMake <1%
  • Shell <1%

Topics

  • quantization
  • deep-learning
  • compression
  • open-source
  • machine-learning
  • pruning
  • auto-ml
  • network-compression
  • deep-neural-networks
  • network-quantization
  • opensource

Project record

  • JobOther AI tools
  • StatusListed
  • Commits4,379
  • Forks478
  • Watching46
  • Stars in 28 days+21
  • CreatedApr 21, 2020
  • First seen by usNov 7, 2026
  • CheckedNov 12, 2026

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