Random Sentiment Analysis with Huggingface Transformers

This function uses the pipeline feature from the Huggingface Transformers library to randomly select a pre-trained model for sentiment analysis, performs sentiment analysis on the input text, and returns the analysis result.

Technology Stack : Huggingface Transformers

Code Type : The type of code

Code Difficulty : Intermediate

                
                    
def generate_random_sentiment_analysis(arg1, arg2):
    import random
    from transformers import pipeline

    # Select a random pre-trained model for sentiment analysis
    models = ["distilbert-base-uncased-finetuned-sst-2-english", "roberta-large-mnli", "xlnet-large-qna",
              "bert-base-cased-finetuned-sst-2-english", "albert-large-v2"]
    selected_model = random.choice(models)

    # Create a sentiment analysis pipeline
    nlp = pipeline("sentiment-analysis", model=selected_model)

    # Perform sentiment analysis on the input text
    result = nlp(arg1)

    # Return the sentiment analysis result
    return result