How to go about creating embeddings (especially, token to Id mapping) for categorical columns in tensorflow 2.0+?
Embedding() layers take sequences as inputs. If there is no time dependency in your data (such as for time series datasets or language corpora) then those layers cannot be used. What kind of data do you have?

Alternatively, you can use dimensionality reduction, one-hot encoding or, in some cases, label encoding. I personally suggest dimensionality reduction whenever possible, even if it's the most computationally intensive choice.