This is the Linux app named Magika whose latest release can be downloaded as magika-x86_64-apple-darwin.tar.xz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Magika with OnWorks for free.
Suivez ces instructions pour exécuter cette application :
- 1. Téléchargé cette application sur votre PC.
- 2. Entrez dans notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous voulez.
- 3. Téléchargez cette application dans ce gestionnaire de fichiers.
- 4. Démarrez l'émulateur en ligne OnWorks Linux ou Windows en ligne ou l'émulateur en ligne MACOS à partir de ce site Web.
- 5. Depuis le système d'exploitation OnWorks Linux que vous venez de démarrer, accédez à notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous souhaitez.
- 6. Téléchargez l'application, installez-la et exécutez-la.
CAPTURES D'ÉCRAN
Ad
Magique
DESCRIPTION
Magika is an AI-powered file-type detector that uses a compact deep-learning model to classify binary and textual files with high accuracy and very low latency. The model is engineered to be only a few megabytes and to run quickly even on CPU-only systems, making it practical for desktop apps, servers, and security pipelines. Magika ships as a command-line tool and a library, providing drop-in detection that improves on traditional “magic number” and heuristic approaches, especially for ambiguous or short files. The project documentation highlights how the model is trained and optimized, and how its inference path enables millisecond-level classification. It also emphasizes reproducibility and developer ergonomics with clear install and usage instructions for common platforms. A public site complements the repo with background, examples, and guidance for integrating Magika into existing workflows.
Comment ça marche
- Tiny deep-learning model that runs in milliseconds on CPU
- CLI and library APIs for easy integration
- High accuracy on tricky or ambiguous file samples
- Works across binary and textual content types
- Reproducible installs with clear usage examples
- Practical replacement for heuristic magic-based detectors
Langage de programmation
Python
Catégories
This is an application that can also be fetched from https://sourceforge.net/projects/magika.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
