LLM Next Token Prediction with PyTorch

Implement a Next Token Prediction for a Large Language Model (LLM) using PyTorch. Create a simple fake dataset for training and ensure the model performs accurate predictions. Requirements: Use PyTorch to implement the model. Create a simple fake dataset by yourself. Demonstrate the training process live. Test Cases: Test the model with the dataset {input_sequence: 'hello world', expected_output: 'world after'} to ensure correct output. Test if batch input data successfully trains the model. Validate the model's prediction accuracy with given input sequences like ['this is', 'a test']. Check edge cases such as empty input. Observe the impact of long sequence inputs on the model. Example Input hello world