Ludwig provides a low code framework for building custom LLMs, neural networks, and other AI models.
N2D2
N2D2 provides an open source CAD framework for deep neural network simulation and application building.

About N2D2
N2D2, short for Neural Network Design & Deployment, is CEA-LIST's open source CAD framework for designing and simulating deep neural networks and building full DNN-based applications on embedded platforms. It is released under the CeCILL-C license, a free software license compatible with GNU/LGPL, so the license terms should be checked before use.
Pricing is not clearly stated.
Key features
- Pre-built Docker image on Docker Hub
- Source build with CMake and make on Linux
- Python API installation guide
- Online documentation for usage
- CUDA support can be disabled with an environment variable
- OpenCV and Gnuplot are mandatory dependencies
- GPU acceleration needs NVIDIA CUDA and CuDNN
- CUDA and CuDNN version requirements differ by platform
- Linux source builds require manual compilation steps
N2D2 at a glance
- Website
- github.com/CEA-LIST/N2D2
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Platforms
- Linux, Windows
- Details verified
- Oct 21, 2026 · Official source
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Sinabs supports fast training of spiking neural networks with PyTorch and inference on neuromorphic hardware.
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