chrhenning/hypnettorch

Package for working with hypernetworks in PyTorch.

49
/ 100
Emerging

This package helps machine learning researchers and practitioners implement and experiment with hypernetworks in PyTorch. It takes a base neural network architecture as input and generates its weights using a hypernetwork, enabling advanced deep learning techniques. This is designed for those exploring complex neural network structures and continual learning.

132 stars. No commits in the last 6 months. Available on PyPI.

Use this if you are a machine learning researcher or engineer working with PyTorch and need tools to easily build and integrate hypernetworks into your models.

Not ideal if you are looking for a high-level, off-the-shelf solution for common machine learning tasks without diving into the specifics of neural network architectures.

deep-learning-research neural-network-architecture continual-learning model-generation machine-learning-engineering
Stale 6m No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 14 / 25

How are scores calculated?

Stars

132

Forks

15

Language

Python

License

Apache-2.0

Last pushed

Sep 07, 2023

Commits (30d)

0

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