How would you fix syntax errors when training a transformer model for code generation tasks

Question

Can you tell me How would you fix syntax errors when training a transformer model for code generation tasks?

Answer 1

Syntax errors in code generation tasks can be reduced by using curated training data, applying syntax-aware tokenizers, and validating outputs with parsers.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Uses a pre-trained GPT model for code generation.
• Validates the generated code with Python’s built-in ast module to catch syntax errors.
• Ensures clean and executable code by filtering outputs with syntax checks.

Hence, combining transformer-based generation with syntax validation ensures that the generated code is syntactically correct and ready for execution.