01 / Technologies / AI / ML

Detect TensorFlow in any GitHub repo

TensorFlow is one of the ai / ml technologies Stack Fingerprint recognises automatically when it scans a public repository.

How TensorFlow is detected

Stack Fingerprint reads the repo's full file tree in one GitHub API call and flags TensorFlow when it finds any of these:

  • Dependencies in Python (requirements.txt / pyproject.toml): tensorflow

TensorFlow README badge

A static badge you can paste anywhere in Markdown:

TensorFlow badge

Markdown
![TensorFlow](https://img.shields.io/badge/TensorFlow-FF6F00?style=for-the-badge&logo=tensorflow&logoColor=white)

Or let the repo describe itself

Static badges go stale the moment you swap a dependency. A Stack Fingerprint card is generated from the repo, so TensorFlow (and everything around it) appears or disappears on its own:

README.md
[![Stack Fingerprint](https://stackfingerprint.vercel.app/api/card?repo=OWNER/REPO)](https://stackfingerprint.vercel.app/?repo=OWNER/REPO)

Replace OWNER/REPO with your repository, or open the builder to pick a theme and layout.