Creating Model Instances and Initializing a Simple Model

This function creates an instance from a given sentence and vocabulary, and initializes a simple model. It first converts the sentence into a format that the model can understand, then creates a model with basic parameters.

Technology Stack : Allennlp

Code Type : Function

Code Difficulty : Intermediate

                
                    
from allennlp.models import Model
from allennlp.data import Instance
from allennlp.data.vocabulary import Vocabulary
from allennlp.nn.util import get_text_field_mask

def create_instance_and_model(vocab: Vocabulary, sentence: str):
    # Create an instance from a sentence
    instance = Instance(
        text_field=Instance.from_tensor_dict({
            'tokens': vocab.get_token_ids_from_strings([sentence]),
            'token_mask': get_text_field_mask(vocab.get_token_ids_from_strings([sentence]))
        })
    )
    # Create a simple model for demonstration purposes
    model = Model.from_params(
        params={"text_field_embedder": {"token_embedder": {"embedding_dim": 10}}}
    )
    return instance, model