Allennlp-Based Sentence Classification with Pre-Trained Model

This function takes a list of sentences and a label, and classifies the sentences using a pre-trained model from the Allennlp library.

Technology Stack : Allennlp

Code Type : Text classification function

Code Difficulty : Intermediate

                
                    
import random
import allennlp.nn.util as nn_utils
from allennlp.data import Instance
from allennlp.data.fields import TextField, LabelField

def random_sentence_classification(arg1, arg2):
    # This function takes in a list of sentences and a label and classifies the sentences
    # based on the provided label using a pre-trained model from the Allennlp library.

    # arg1 is a list of sentences to classify
    # arg2 is the label for the sentences

    # Create a list of text fields for the sentences
    text_fields = [TextField(sentence) for sentence in arg1]

    # Create an instance with the text fields and the label field
    instance = Instance({'text': text_fields}, label=LabelField(arg2))

    # Load a pre-trained model (this is a placeholder; in practice, you would load a specific model)
    model = nn_utils.load_pretrained_model("srl-model")

    # Use the model to predict the labels for the sentences
    predictions = model.predict_instance(instance)

    # Return the predictions
    return predictions