Text Generation Using GPT-2

To fine-tune the GPT-2 model using the complete works of Shakespeare.

Dataset Preparation: Collecting and preparing the complete works of Shakespeare for training.

Data Preprocessing: by creating a tokenizer, encoding the text, and batching the dataset.

Model Fine-Tuning: Load a pre-trained GPT-2 model using the transformers library. Set up the training loop, including defining the optimizer and loss function. Train the model on the Shakespeare Dataset.

Evaluation: Generate some text using the trained model. Establishing metrics for evaluating the success of the fine-tuning in emulating Shakespearean style.

GPT-2 Model

Python for scripting

Various NLP and machine learning libraries like TensorFlow, PyTorch, and Hugging Face Transformers.