I haven’t found doc on how to use `tfjs.converters`

directly, but I was able to go beyond the `tensorflow_text`

with the following code (based on the logic of the CLI converter):

```
import tensorflow as tf
import tensorflowjs as tfjs
import tensorflow_hub as hub
import tensorflow_text
from tensorflowjs.converters import tf_saved_model_conversion_v2
tf_saved_model_conversion_v2.convert_tf_hub_module(
"https://tfhub.dev/google/universal-sentence-encoder-multilingual/3",
"web_model",
signature="serving_default"
)
```

However, I now get the following error:

```
ValueError: Unsupported Ops in the model before optimization
SentencepieceOp, SegmentSum, RaggedTensorToSparse, ParallelDynamicStitch, SentencepieceTokenizeOp, DynamicPartition
```

It seems that this multilingual model uses different operators than the universal sentence encoder provided of TF.js model’s page.