Refactor Transformer Models & Extend Encoder-Decoder Support

[JulesBelveze]

Description

This pull request introduces significant changes to the Transformer-based modules within the bert_squeeze package. Refactoring was performed to streamline model instantiation, and new features were added for better integration of encoder-decoder models, especially custom ones.

Changelog

Features

• Extend BaseEncoderDecoderModel to support VisionEncoderDecoder, allowing initialization from custom encoder and decoder or pre-trained vision models.
• Implement EncoderDecoderModel class to allow loading of pre-trained transformer checkpoints and provide methods for replacing encoder and decoder instances.

Refactors

• Introduce BASE_CLASS_MODEL for better instantiation of Transformer-based modules and remove the need for _build_model method, hence simplifying the model architecture.
• Remove unnecessary @overrides decorators from model classes.
• Pass an optional instantiated model to BaseTransformerModule constructors for enhanced flexibility.
• Modified configuration files to point to the correct targets after structural changes.
• Simplify the forward method and add generate methods for BaseEncoderDecoderModel.
• Introduce an optional model parameter in the SimpleT5Model constructor for more streamlined instantiation.

Test Updates

• Update existing tests to adhere to the new model structure.
• Add a new test case for the T5 summarization with a custom BaseEncoderDecoderModel.