Rust Lighter

This project was started as my RUST exercise to abstract the Rust minimalist ML framework Candle (https://github.com/huggingface/candle) and introduce a more convenient way of programming neural network machine learning models.

The behaviour is inspired by Python KERAS (https://keras.io) and the initial step based on the Rust-Keras-like code (https://github.com/AhmedBoin/Rust-Keras-Like).

So let's call the project Candle Lighter 🕯, because it helps to turn on the candle light and is even easier to implement.

Examples can be found below the lib/examples/ directory.

To use it as library just call 'cargo add candlelighter'

MAINTAINERS AND CONTRIBUTORS ARE HIGHLY WELCOME

Note: It is by far not production ready and is only used for own training purposes. No warranty and liability is given. I am a private person and not targeting any commercial benefits.

Supported Layer types

Meta Layer	Type	State	Example
Sequential model	-	✅
-	Feature scaling	🏃	DNN and TNN
-	Dense	✅	DNN
-	Convolution	✅	CNN
-	Pooling	✅	-
-	Normalization	✅	-
-	Flatten	✅	-
-	Recurrent	✅	RNN 1st throw
-	Regulation	✅	-
-	Recurrent	✅	RNN 1st throw
-	Autoencoder	🏃	-
-	Feature embedding	✅	S2S 1st throw
-	Attention	🏃	TNN 1st throw
-	Mixture of Experts	🏃	ENN 1st throw
-	Feature masking and -quantization	🏃	-
Parallel model (in sense of split)	-	🏃	PNN 1st throw
Parallel model	Merging	🏃	PNN 1st throw
-	Model fine tuning	🏃	DNN2 & DNN3
Transformer models	see	🏃
* BERT	Text similarity	✅	LLM
Reinforcement models	see	🏃

License

Tripple-licensed to be compatible with the Rust project and the source roots.

Licensed under the MPL 2.0, MIT license or the Apache license, Version 2.0 at your option.