Random Model Text Generation with Huggingface Transformers

This function uses a pre-trained model from the Huggingface Transformers library to generate text. The user inputs a prompt, and the function randomly selects a pre-trained model to generate text based on the prompt.

Technology Stack : Huggingface Transformers, text generation

Code Type : The type of code

Code Difficulty : Advanced

                
                    
def generate_random_text(prompt, max_length=50):
    import random
    from transformers import pipeline

    # Select a random model from the Huggingface Transformers library
    models = ["distilgpt2", "gpt2", "t5", "bert-base-chinese", "roberta-base"]
    model_name = random.choice(models)
    
    # Load the selected model
    generator = pipeline("text-generation", model=model_name)

    # Generate text based on the prompt
    response = generator(prompt, max_length=max_length, return_full_text=False)[0]

    return response["generated_text"]