Using in production¶

Unitxt can be used to process data in production. First define a recipe:

recipe = "card=cards.wnli,template=templates.classification.multi_class.relation.default,demos_pool_size=5,num_demos=2"

Second prepare an instance in the exact schema of the task in that recipe:

instance = {
  "label": "?",
  "text_a": "It works perfectly",
  "text_b": "It works!",
  "classes": ["entailment", "not entailment"],
  "type_of_relation": "entailment",
  "text_a_type": "premise",
  "text_b_type": "hypothesis",
}

Then you can produce that model-ready data with the produce function:

from unitxt import produce

result = produce([instance], recipe)

Then you have the production ready instance in the result. If you print(result[0][“source”]) you will get:

Given a premise and hypothesis classify the entailment of the hypothesis to one of entailment, not entailment.

premise: When Tatyana reached the cabin, her mother was sleeping. She was careful not to disturb her, undressing and climbing back into her berth., hypothesis: mother was careful not to disturb her, undressing and climbing back into her berth.
The entailment class is entailment

premise: The police arrested all of the gang members. They were trying to stop the drug trade in the neighborhood., hypothesis: The police were trying to stop the drug trade in the neighborhood.
The entailment class is not entailment

premise: It works perfectly, hypothesis: It works!
The entailment class is