Workaround HF Quantizer apply_quantization_config misuse

[kylesayrs]

CompressedTensorsHfQuantizer attempts to use apply_quantization_config to apply the quantization config to the model

def _process_model_before_weight_loading(self, model, **kwargs):
        from compressed_tensors.quantization import apply_quantization_config

        ct_quantization_config = self.compressor.quantization_config
        apply_quantization_config(model, ct_quantization_config, run_compressed=True)

However, self.compressor.quantization_config can be None in the case that only sparsity is present. This does not align with the function contract of apply_quantization_config. In such a case, an error is thrown.

def apply_quantization_config(
    model: Module, config: QuantizationConfig, run_compressed: bool = False
) -> Dict:

This PR adjusts the function to handle Nones until this branch's changes are landed on transformers

[dsikka]

Add a comment for when this would be the case for clarity

[rahul-tuli]

This is needed!