Training GPT, a deep learning model, to generate personalized text recommendations for creative hobbies and artistic expression involves several challenges:
1. Fine-tuning for specific tasks: GPT needs to be trained on a diverse set of data related to creative hobbies and artistic expression to provide accurate recommendations.
2. Addressing biased output: GPT may generate biased or inappropriate text, requiring meticulous monitoring and editing of the model’s output.
3. Data quality and diversity: Ensuring the training data is of high quality and diverse is crucial for GPT to provide relevant and personalized recommendations.