TARS Zero Shot Classifier Predictions

[nlproc-007]

Here is the example code to use TARS Zero Shot Classifier

from flair.models import TARSClassifier
from flair.data import Sentence

# 1. Load our pre-trained TARS model for English
tars = TARSClassifier.load('tars-base')

# 2. Prepare a test sentence
sentence = Sentence("I am so glad you liked it!")

# 3. Define some classes that you want to predict using descriptive names
classes = ["happy", "sad"]

#4. Predict for these classes
tars.predict_zero_shot(sentence, classes)

# Print sentence with predicted labels
print(sentence)
print(sentence.labels[0].value)
print(round(sentence.labels[0].score,2))

Now this code is wrapped into the following function so that I can use it to get predictions for multiple sentences in a dataset.

def tars_zero(example):
  sentence = Sentence(example)
  tars.predict_zero_shot(sentence,classes)
  print(sentence)

inputs = ["I am so glad you liked it!", "I hate it"]
for input in inputs:
  tars_zero(input)

#output: 
Sentence: "I am so glad you liked it !" → happy (0.8667)
Sentence: "I hate it"

Here the model is giving predictions only for the first instance.

[helpmefindaname]

Hi @nlproc-007 does tars.predict_zero_shot(sentence, classes, multi_label=False) work?

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