Add Yaml Config

# Yaml file

## Premise
The Yaml File should structure their projects with the proper dependencies, integrations, and template code based on the settings provided.

## Future
- In the future, you can use this to pull other user's code and train them just by modifying some settings in the YAML.
- You should also be able to detail cloud settings from this file alone and start cloud training sessions.

## Implementation

The Yaml File will hold configuration details on the project, that can be used to streamline the model training process.

In the file, you will detail:
- Which framework to use: PyTorch, TensorFlow, JAX, ...
- The type of model that is being used: LLM, YOLO, ...
- the actions you wish to perform Train, Deploy, FineTune
- The distributed framework being used: Accelerate, Horovod, DDP, None
- Distributed Settings File
- additional dependencies
- dataset configurations

The same configuration should be able to be done without a YAML simply through an object