If your goal is to get the network as small as possible, you could try using NEAT[1]. A cool example of a small network for a hard task using NEAT is MarI/O[2].
- 14 Bytes does not include the runtime!
- All that counts towards the 14 Bytes is the model weights
- Lack of git history is because my actual repo is private, this is just the frontend for now + models
If your goal is to get the network as small as possible, you could try using NEAT[1]. A cool example of a small network for a hard task using NEAT is MarI/O[2].
[1]: https://en.wikipedia.org/wiki/Neuroevolution_of_augmenting_t...
[2]: https://www.youtube.com/watch?v=qv6UVOQ0F44
I would love to understand what the inputs actually are. Very neat visualization.
Facts:
- 14 Bytes does not include the runtime! - All that counts towards the 14 Bytes is the model weights - Lack of git history is because my actual repo is private, this is just the frontend for now + models