feature: ONNX service with multiple inputs

[wyhanz]

Feature request

I exported an onnx model that accept multiple inputs ("input_ids", "input_mask", "input_seg").

And the docs for bentoml(ONNX) only give a simple example, runner.run.run(test_input). However, an error ouccred after i wrapped these inputs with dict:
TypeError: run of ONNXRunnable only takes numpy.ndarray or pd.DataFrame, tf.Tensor, or torch.Tensor as input parameters

I wonder if i use it in a wrong way?

Motivation

I think ONNX is useful for AI inference so can you improve the docs about using bentoml on onnx service?

Other

No response