Random Sentiment Analysis Model Selection

This function randomly selects a sentiment analysis model from the Huggingface Transformers library and creates a sentiment analysis pipeline. Then, it defines an internal function `sentence_analysis` which takes a piece of text and performs sentiment analysis using the pipeline.

Technology Stack : Huggingface Transformers

Code Type : Custom function

Code Difficulty : Intermediate

                
                    
import random
from transformers import pipeline

def generate_random_sentiment_analysis():
    # Randomly select a sentiment analysis model from the Huggingface Transformers library
    models = ["distilbert-base-uncased-finetuned-sst-2-english", "roberta-large-mnli"]
    model_name = random.choice(models)
    
    # Create a sentiment analysis pipeline using the selected model
    nlp = pipeline("sentiment-analysis", model=model_name)
    
    def sentiment_analysis(text):
        # Use the sentiment analysis pipeline to predict the sentiment of the input text
        return nlp(text)
    
    return sentiment_analysis

# Example usage
analysis = generate_random_sentiment_analysis()
print(analysis("I love this product!"))