Added scripts on how to use the library for recsys in response to issue #133. Also Added a simple/basic transformer model for the text component before integrating with HF. Also added the option of specify the dimension of the feed forward network

first step towards adding an example on how to reproduce a kaggle notebook (details in the code) with this library

removed all partial imports and all import * with the aim of avoiding potential circular imports issues and increase readability. Fixed a couple bugs along the way

Manually bringing all the mkdocs changes to the self supervised branched as the conflicts were somehow too much to make it happen via sublime merge or vscode...I am at utils. After this we need to test callbacks for self supervised. Then the usual overall checks and install checks and make the massive release

Added Self Supervised Pretraining for all tabular models. Need to unit test and surely there will be some code readjustments

Self Supervised Runs for all attention based models. Whether it learns something or not, is a question we still need to answer

Adjusted output and encoder_output dims so that all models can be used with self supervised training

Added two base classes for the tabular models and allowed for bias and activations for the categorical embeddings