You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I would like to implement LongNet for a project that is inputting numerical data into a transformer, to predict numerical data. However, for my data there are connections between each data point in the input sequence over the entire range of the input.
This means that segment lengths and dilation rates chosen by a human user might not make sense. So I wanted to ask if there is a way of learning the best segment lengths and dilation rates, based on the connections in the input sequence that the model might find?
Many thanks.
The text was updated successfully, but these errors were encountered:
benrousePUC
changed the title
Question about learnable segments lengths and dilation rates
Question about learnable segment lengths and dilation rates
Apr 10, 2024
Hi there,
I would like to implement LongNet for a project that is inputting numerical data into a transformer, to predict numerical data. However, for my data there are connections between each data point in the input sequence over the entire range of the input.
This means that segment lengths and dilation rates chosen by a human user might not make sense. So I wanted to ask if there is a way of learning the best segment lengths and dilation rates, based on the connections in the input sequence that the model might find?
Many thanks.
The text was updated successfully, but these errors were encountered: