Implement zero-shot learning on text to predict semantic relationships
$30-250 USD
Pago na entrega
I have triples such as:
(Justin - likes - apples)
(apples - color - red)
I would like to train such data using zero-shot learning to build a model to predict the relationship (second term in the triple). Zero-shot model known for the ability to predict objects that do not exist in the training set and that is what I want. For example, given the triple (man - .... - USA) the model should predict (lives) even if the relationship (lives) did not appear in the training data.
All the code should be using Python3.
ID do Projeto: #18309196
Sobre o projeto
8 freelancers estão ofertando em média $237 nesse trabalho
I am expert who understands the value of time. I pride myself in my attention to detail. I am very hard working and aim to deliver in less time than quoted. I want to make you, my employer happy without changing my bid Mais
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