In other words, is it possible to train a supervised transformer model to pull out specific from unstructured or semi-structured text and if so, which pretrained model would be best for this?
In the resume example, I’d want to input the text version of a person’s resume and get a json like the following as output: {‘Education’: [‘BS Harvard University 2010’, ‘MS Stanford University 2012’], ‘Experience’: [‘Microsoft, 2012-2016’, ‘Google, 2016 - Present’]}
Obviously, I’ll need to label hundreds or thousands of resumes with their relevant Education and Experience fields before I’ll have a model that is capable of the above.
Here’s another example 32 of the solution that I’m talking about although this person seems to be using GPT-3 and didn’t have any code provided.  Is this something that any of the huggingface pipelines 8 is capable of and if so, which pipeline would be most appropriate?