# prompt_strategies.stepwise_supervised – Axolotl

# prompt_strategies.stepwise_supervised

`prompt_strategies.stepwise_supervised`

Module for stepwise datasets, typically including a prompt and reasoning traces, and (optionally) per-step, or per-prompt-trace labels for reward modelling.

## Classes

Name | Description
--- | ---
StepwiseSupervisedPromptTokenizingStrategy | Tokenizing strategy for supervised stepwise datasets, typically used for COT-reasoning.

### StepwiseSupervisedPromptTokenizingStrategy

    prompt_strategies.stepwise_supervised.StepwiseSupervisedPromptTokenizingStrategy(
        tokenizer,
        sequence_len=2048,
        step_separator='\n',
        max_completion_length=None,
        train_on_last_step_only=False,
    )

Tokenizing strategy for supervised stepwise datasets, typically used for COT-reasoning. These datasets should include the following columns: - prompt: the prompt text - completions: a list of `n` completion steps - labels: a list of `n` labels indicating the “correctness” of each step