Allow passing model_args to ST

[satyamk7054]

Summary

Allow passing model_args to ST

Details

This fixes #2579.
New models like e5-mistral-7b-instruct use FP16 as the dtype.
However, when loaded using sentence_transformers, they are loaded with FP32. This is because
HF transformers uses FP32 as the default unless torch_dtype='auto' is passed, as mentioned here.

Passing "auto" to model_args does not work because of the below error. Moreover, the SentenceTransformers class does not currently expose a model_args param.

cls = <class 'transformers.models.bert.modeling_bert.BertModel'>, dtype = 'auto'

    @classmethod
    def _set_default_torch_dtype(cls, dtype: torch.dtype) -> torch.dtype:
        """
        Change the default dtype and return the previous one. This is needed when wanting to instantiate the model
        under specific dtype.
    
        Args:
            dtype (`torch.dtype`):
                a floating dtype to set to.
    
        Returns:
            `torch.dtype`: the original `dtype` that can be used to restore `torch.set_default_dtype(dtype)` if it was
            modified. If it wasn't, returns `None`.
    
        Note `set_default_dtype` currently only works with floating-point types and asserts if for example,
        `torch.int64` is passed. So if a non-float `dtype` is passed this functions will throw an exception.
        """
>       if not dtype.is_floating_point:
E       AttributeError: 'str' object has no attribute 'is_floating_point'

../venv/lib/python3.10/site-packages/transformers/modeling_utils.py:1412: AttributeError

Testing Done

Added a new unit tests that validates the dtype of the loaded model using the embedding tensor
created with it.