nirw4nna/dsc

Tensor library & inference framework for machine learning

34
/ 100
Emerging

This project provides a highly efficient library for creating and running machine learning models, similar to PyTorch or NumPy but with enhanced performance. It takes raw data, processes it through neural networks, and outputs predictions or analytical results. Data scientists and machine learning engineers who need to deploy or experiment with models efficiently, especially on diverse hardware, would find this useful.

116 stars. No commits in the last 6 months.

Use this if you are a data scientist or machine learning engineer building and running neural networks and need a highly performant, flexible, and portable framework that can seamlessly switch between CPU and various GPU backends.

Not ideal if you are a beginner looking for a high-level, opinionated machine learning framework with extensive pre-built models and simple one-line installation.

machine-learning neural-networks model-deployment scientific-computing data-processing
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 15 / 25
Community 7 / 25

How are scores calculated?

Stars

116

Forks

5

Language

C++

License

BSD-3-Clause

Last pushed

Oct 03, 2025

Commits (30d)

0

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