Community Ecosystem

See yourself on the TinyTorch Globe! Create an account and join the global community to track your progress and connect with other builders.

Learn together, build together, grow together.

TinyTorch is more than a course—it’s a growing community of students, educators, and ML engineers learning systems engineering from first principles.

Community Dashboard (Available Now)

Join the global TinyTorch community and see your progress:

  1. Create a community account to connect your profile with other builders.
  2. Build and complete modules with tito module start and tito module complete.
  3. Review your progress in the dashboard and run the milestones your modules unlock.
  4. Choose what to share when joining the community.

How to Join the TinyTorch Community:

There are two primary ways to join and engage with the TinyTorch community:

Option 1: Explore the Live Dashboard

You can explore the interactive TinyTorch Community Dashboard directly in your browser:

Explore Dashboard

Option 2: Join via TinyTorch CLI

Download the TinyTorch CLI to set up your environment, manage your profile, and contribute to community statistics directly from your terminal.

# First-time setup (creates your local profile; does not join the community)
tito setup

# Or, if already set up, log in
tito community login

# View your profile
tito community profile

# Check your community status
tito community status

# Open the community map
tito community map

Features:

  • Optional profile - tito setup asks for your name, email, and affiliation; every field can be left at its default
  • Progress tracking - Automatic milestone and module completion tracking
  • Local by default - Your profile is written to ~/.tinytorch/profile.json, and module progress to .tito/ in the project
  • You choose what syncs - Nothing is uploaded until you log in with tito community login. Login shows exactly what a sync sends and asks whether later syncs may run automatically

Privacy. The local profile at ~/.tinytorch/profile.json stores the name, email, and affiliation you enter; all three are optional and default to placeholder values. A sync uploads to the TinyTorch website (tinytorch.netlify.app, backed by Supabase): your account email, used as your user ID; which modules you completed and when; which milestones you unlocked or completed and when; your completion percentage; and your current streak. It never uploads code, notebooks, or test output. When you log in, tito shows this list and asks whether it may sync automatically after you complete a module or milestone (logging in from a terminal that cannot prompt counts as yes). If you agree, or later run tito community sync --enable-auto, it syncs after each completion without asking. If you decline, or run tito community sync --disable-auto, it never syncs on its own and stops asking. If no choice is saved on this machine, tito asks after each completion in a terminal and uploads nothing when it cannot ask. Setting TITO_NO_SYNC=1 turns automatic sync off entirely. tito community sync always uploads on demand.

Check Your Environment Speed

tito benchmark baseline   # times plain NumPy on this machine

tito benchmark baseline times a few NumPy operations (elementwise ops and a matrix multiply on 100×100 arrays, and a two-layer forward pass) and reports each time and their geometric mean. It checks your environment, not your TinyTorch code, and gives no score. Results are saved locally under .tito/benchmarks/; nothing is uploaded, and there is no community leaderboard.

tito benchmark capstone is reserved for measuring your Module 20 model but is not implemented yet: it reports an error, saves nothing, and points you to Module 19’s Benchmark class, which you can run on your model directly.

See TITO CLI Reference for complete command documentation.

For Educators

Teaching TinyTorch in your classroom?

See For Instructors for assignment tiers, nbgrader grading, and when to give students the book.

Recognition & Showcase

Built something impressive with TinyTorch?

Share it with the community:

  • Post in GitHub Discussions under “Show and Tell”
  • Tag us on social media with #TinyTorch

Exceptional projects may be featured:

  • On the TinyTorch website
  • In course examples
  • As reference implementations

Stay Updated

GitHub Watch: Enable notifications for releases and updates

Follow Development: Check GitHub Issues for roadmap and upcoming features

Build ML systems. Learn together. Grow the community.

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