I am very new to nlp so sorry for the question.
I am wondering if there a name for this task and if I can do it in deep learning or even in huggingdace 
Let say I have some sentences, for example:
s1:  I have a dog
s2: I am new to this,
I convert my sentences to  embedded features and now I have an inputs with shape of 1x2048x4 for s1 and 1x2048x5 for s2.
Now I want to classify each word to a category out of 10 categories, so the output will be like:
o1: 1x4x10
and
o1: 1x5x10
the dependency between the word in each sentence is important in the classification. it is kinda like token classification but the labels are not representing the token, but instead the feeling that that word will imply to the sentence.
so the length of input may change and the length of output will change as well, but classes are the same.
Can I do it with transformers and self-attention models? should I look for any specific model or task?
Sorry for the boring question, nlp newbie here with a lot of passion