RaviKiran_assessment

The usage of the Hugging Face Transformers library to perform text generation tasks using pre-trained language models. In "Question 1," two different models, GPT-2 and GPT-Neo, are utilized for text generation based on user prompts. The code loads and initializes these models, encodes user input, and generates text continuations. The generated text is displayed to the user. Response 1 uses GPT-2, while Response 2 and 3 use GPT-Neo with different prompts. In "Question 2," the code focuses on the GPT-Neo model for generating responses to specific input prompts. It loads a GPT-Neo model and tokenizer, processes a custom dataset of input-output pairs, and demonstrates how the model generates responses to various prompts. This code showcases the flexibility of pre-trained language models in natural language processing tasks, such as chatbots and question-answering systems.