Time series prediction usage

[SokolOFFF]

Hello!
I have read in your README.md file the next point: "For non language applications or for integrating in other architectures you can use the xLSTMBlockStack". I have an issue now: I want to use your xlstm implementation for time series data prediction, however, I have met problems with "embeddings" while using "xLSTMBlockStack". Based on what should I define "embedding_dim" variable in config? Can you please elaborate on this topic?
Thank you in advance.

[SummerSigh]

If your doing time series of continuous numbers, you should remove the embedding layer. embedding layers are meant to take discrete numbers (like a token lets say 3345) and convert them to a floating point tensor with n_features.

[only1choice]

Hello!
Have you solved this problem?

[zhuwei321]

Have you solved this problem?

[kpoeppel]

The embedding_dim should be seen as synonym for hidden_dim, when you are not using embeddings. The xLSTMBlockStack does not contain embedding/un-embedding layers.