zama-ai / concrete-ml
Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks.
Why this job: works in the areas we cover, but does not say which job it does
What it does
- Built-in models. Ready-to-use FHE-friendly models with a user interface that is equivalent to their the scikit-learn and XGBoost counterparts
- Customs models. Concrete ML supports models that can use quantization-aware training. These are developed by the user using PyTorch or keras/tensorflow and are imported into Concrete ML through ONNX
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Inactive
- Last commit 9 months ago
- Stars
- 1,457
- On GitHub
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- v1.9.0
- Released 19 months ago
- Built with
- Python
- 50% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 85% closed
- 17 still open
- Pull requests
- 778 merged
- 5 waiting
- Releases
- 32
- 0 in the last year
- Contributing guide (opens in new tab)
- No security policy
- Code of conduct (opens in new tab)
Similar repos
| Repo | Stars | Last commit | Licence | Downloads for |
|---|---|---|---|---|
| tensorflow / privacy | 2,037 | 3 days ago | Apache-2.0 | No downloads |
More: languages, topics and project record
Languages
- Python 50%
- Jupyter Notebook 48%
- Shell 1%
- Makefile 1%
Topics
- python
- data-science
- privacy
- torch
- scikit-learn
- homomorphic-encryption
- machine-learning
- fhe
- tfhe
- ppml
- fully-homomorphic-encryption
Project record
- JobOther AI tools
- StatusListed
- Commits2,051
- Forks202
- Watching23
- Stars in 28 days+1
- CreatedMar 23, 2022
- First seen by usNov 7, 2026
- CheckedNov 8, 2026