• BaseProcessor: The base class for dataset post-processing.
• TextualizeProcessor: Transforms all datasets into a consistent text-to-text generation format.

• Import the Module:

from prompt2model.dataset_processor.textualize import TextualizeProcessor

• Initialize TextualizeProcessor:

processor = TextualizeProcessor(has_encoder=<True/False>)
# <True/False>: Whether the model you want to finetune has an encoder.

Choose encoder type:

• has_encoder=True for encoder-decoder models (e.g., T5).

• has_encoder=False for decoder-only/autoregressive models (e.g., GPT2).

• Process Datasets:

instruction = "<your-instruction>"
dataset_dicts = [...]  # List of DatasetDict
modified_dataset_dicts = processor.process_dataset_dict(instruction, dataset_dicts)