mirror of https://github.com/luxfi/torus-ml.git synced 2026-10-30 15:15:23 +00:00

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zeekay e037e8f7ea torus: one name for the package, and it is ours

The distribution called itself torus-ml while shipping a package directory
named concrete, so the name a user installs and the name they import disagreed
— and most of the tree already said torus.ml, which could not resolve against
src/concrete. Moved src/concrete to src/torus and pointed the include at it.

The dependency was Zama's concrete-python from their index. It is torus-fhe
from ours, which is what luxfhe/torus already ships: that frontend declares
torus-fhe and ships a torus/fhe module, so every 'from torus.fhe' in this tree
was already naming our compiler and only the dependency lagged.

Two distributions share one namespace, which is the shape the upstream this
forked from used and the reason the split works: torus-fhe gives torus.fhe,
torus-ml gives torus.ml.

Swept every other spelling — identifiers, enum members, workflow variables,
filenames, notebooks. LICENSE and NOTICE keep the upstream attribution a fork
owes; the figures carry the old name in JPEG metadata a text sweep cannot
reach.

2026-08-27 13:20:50 -07:00

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description, layout

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Torus ML is an open-source, privacy-preserving, machine learning framework based on Fully Homomorphic Encryption (FHE).

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Welcome

Get started

Learn the basics of Torus ML, set it up, and make it run with ease.


What is Torus ML	Understand the Torus ML library with a full example.	start1.png	getting-started
Installation	Follow the step-by-step guide to install Torus ML in your project.	start2.png	pip_installing.md
Key concepts	Understand important cryptographic concepts to implement Torus ML.	start3.png	concepts.md

Build with Torus ML

Start building with Torus ML by exploring its core features, discovering essential guides, and learning more with user-friendly tutorials.


Fundamentals	Explore core features.	Built-in models Deep learning	build1.png
Guides	Deploy your projects.	Prediction with FHE Production deployment	build2.png
Tutorials	Learn more with tutorials.	Start here Go further	build3.png

Explore more

Access to additional resources and join the Lux community.

References & Explanations

Refer to the API, review product architecture, and access additional resources for in-depth explanations while working with Torus ML.

Support channels

Ask technical questions and discuss with the community. Our team of experts usually answers within 24 hours in working days.

Community channels

Developers

Collaborate with us to advance the FHE spaces and drive innovation together.

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