Random Model Prediction with Allennlp

This function randomly selects a dataset reader, a model, and a predictor from the Allennlp library, and then uses these components to make a prediction on a given instance of the dataset.

Technology Stack : Allennlp

Code Type : The type of code

Code Difficulty : Intermediate

                
                    
import random
from allennlp.models import Model
from allennlp.predictors import Predictor
from allennlp.data import Instance, DatasetReader, Vocabulary

def random_model_prediction():
    # Select a random dataset reader
    dataset_reader = random.choice([
        DatasetReader("atis"),
        DatasetReader("squad"),
        DatasetReader("mnli")
    ])

    # Load the dataset
    dataset = dataset_reader.read("path_to_dataset")

    # Select a random model
    model = random.choice([
        Model.load("path_to_model_atis"),
        Model.load("path_to_model_squad"),
        Model.load("path_to_model_mnli")
    ])

    # Create an instance
    instance = dataset[0]

    # Create a predictor
    predictor = Predictor.from_model(model)

    # Make a prediction
    prediction = predictor.predict(instance)

    return prediction