Ray2333/Gpt2 Large Helpful Reward Model

The repository lacks detailed examples and explanations for fine-tuning the model beyond basic text classification tasks.

Model training times significantly increase with larger datasets, making it less suitable for real-time or high-throughput applications.

The model is tightly coupled with the Hugging Face Transformers library and its dependencies, limiting flexibility and introducing potential versioning conflicts.

Generating helpful responses requires significant computational resources, which can be costly at scale or prohibitive for resource-constrained environments.