archai
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
GraphCanon updated today · GitHub synced today
Trust & integrity
Full report- Maintenance
- Slowing (229d since push)
- As of today · Source: github_public_v1
- Provenance
- Not a fork · Organization account
- As of today · Source: github_public_v1
- Security (OSV)
- No lockfile
- As of today · Source: none
Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.
Backing
Company and funding context for Microsoft. Display-only - not part of trust score or organic ranking.
- Company
- Microsoft·GitHub org profile·today
- Employees
- 221,000·Wikidata (P1128 employees)·today
- Commercial model
- Pure OSS·GitHub org profile (public repos)·today
Overview
Archai is a tool designed to streamline the process of Neural Architecture Search (NAS) by providing fast, reproducible, and modular capabilities for researchers in automated machine learning and deep learning domains.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Jul 12, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 11, 2026)
**Archai requires Python 3.8+ and PyTorch 1.7.0+ to function properly.**Source link
Tags
README
Installation
Archai can be installed through various methods, however, it is recommended to utilize a virtual environment such as conda or pyenv for optimal results.
To install Archai via PyPI, the following command can be executed:
pip install archai
Archai requires Python 3.8+ and PyTorch 1.7.0+ to function properly.
For further information, please consult the installation guide.
License
This project is released under the MIT License. Please review the file for more details.