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Introduction to the Neural Magic Documentation Project

The Neural Magic Documentation project is a key resource for users interested in exploring, building, and executing high-performance deep learning models on CPU resources. Neural Magic, Inc. has crafted this platform to deliver a suite of software components aimed at optimizing deep learning processes by effectively utilizing CPUs, bypassing the traditional necessity for GPUs.

Key Components and Features

The documentation platform serves as a gateway to various Neural Magic products, each designed to address specific aspects of deep learning models. Here's a brief look at the products detailed in the documentation:

• SparseML: This toolkit provides powerful utilities for optimizing and deploying machine learning models by exploiting sparsity, which helps reduce the resource demands of models while maintaining performance. SparseML comprises its own GitHub repository where users can track issues, contribute, and access the latest releases.

• Sparsify: Aiming at simplifying the model optimization process, Sparsify offers intuitive interfaces to transform existing models into sparse models, thereby enhancing their efficiency and inference speed. Like SparseML, Sparsify maintains a dedicated GitHub repository.

• SparseZoo: This library offers a comprehensive collection of sparse models and optimizations, serving as a valuable repository for those seeking pre-optimized models or inspiration for custom model design.

• DeepSparse Community and Enterprise: The DeepSparse engine is tailored to run optimized models on x86 CPUs for community users and offers an enterprise-grade product for business use. The Community version provides an opportunity for enthusiasts to experiment and utilize cutting-edge sparsity techniques in their workflows.

Getting Involved

For those who are curious about integrating into the Neural Magic ecosystem or eager to contribute, joining the Neural Magic Community Slack is highly encouraged. It is a thriving hub where community members can ask questions, share experiences, and contribute to ongoing discussions. In addition, finding solutions or contributing to developments can be streamlined by accessing the GitHub Issue Queues pertinent to each software repository.

Contribution and Collaboration

The Neural Magic documentation is open to enhancements and improvements from the community. Prospective contributors can:

1. Submit issues on GitHub with the documentation label to propose changes or highlight areas for improvement.
2. Make direct changes via pull requests, ensuring contributions align with the guidelines provided on GitHub.

Technical Foundation

The website itself is built with Docusaurus, a robust and modern static site generator. For developers looking to contribute to the website's development or set up their local development environment, the process is straightforward:

• Installation: Simply run $ yarn to install necessary packages.
• Local Development: Execute $ yarn start to start a live development server and view changes in real-time.
• Building and Deployment: Utilize $ yarn build for generating static content ready for deployment. Deploying the site can be done using SSH or GitHub pages, with respective commands provided in the documentation.

Overall, the Neural Magic Documentation project serves as a comprehensive guide and support system for those interested in harnessing the power of CPU-optimized deep learning models. It's a collaborative and dynamic resource continuously shaped and enhanced by its user community.