Hi, I have a dataset which contains continuous values [ batch_size, features ]
Features look like this :
[0.49221584, -0.021571456, -0.0920076, -0.14408934, -0.62306774]
I want to apply transformer model on these values and pass it to the final layer, something like this
batch_data ==> Transformer ==> output_layer ==> classification
Currently, I am using hand-coded multi-head attention and norm with the feed-forward network to pass these values to the transformer block.
I went through huggingface models, but all the models accept tokens and sequences, Is there any way/hack How I can use hugging face transformer models on direct continuous values?
Looking for TensorFlow/Keras quick template to start with continuous values, that’d be helpful.