[Feature Request][Tracking]: Use accelerate from Hugging Face to optimize loading Pytorch models

### What would you like to happen?

[Accelerate](https://huggingface.co/blog/accelerate-large-models) module from HuggingFace is used to optimize model loading for PyTorch, Tensorflow.

The model loading pipeline in torch happens as below
* Create the model
* Load in memory its weights (in an object usually called state_dict)
* Load those weights in the created model
* Move the model on the device for inference

This is not a smart way to load the model and HuggingFace accelerate helps mitigate this issue.
As per [documentation](https://huggingface.co/docs/accelerate/usage_guides/big_modeling#limits-and-further-development), this is still in development and needs at least one GPU to run this API but as per the docs this could be fixed in the future.

### Issue Priority

Priority: 3

### Issue Component

Component: run-inference