README.md

---
dataset_info:
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 26636179
    num_examples: 18436
  download_size: 4501319
  dataset_size: 26636179
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---


# SFT Format Dataset

## Overview
This dataset is converted to SFT (Supervised Fine-Tuning) format. It was created by transforming OpenMathInstruct and Stanford Human Preferences (SHP) datasets.

## Dataset Structure
Each entry follows this format:

Instruction:
[Problem, question, or conversation history]

Response:
[Solution, answer, or response]

## Usage Guide

### Loading the Dataset
```python
from datasets import load_dataset

# Load datasets from Hugging Face
openmath_train = load_dataset("Seono/sft-openmath-train")
openmath_eval = load_dataset("Seono/sft-openmath-eval")
shp_train = load_dataset("Seono/sft-shp-train")
shp_eval = load_dataset("Seono/sft-shp-eval")


Using for Fine-tuning

# Setting for SFT Trainer
trainer = SFTTrainer(
    model=model,
    tokenizer=tokenizer,
    args=training_args,
    train_dataset=openmath_train["train"],
    dataset_text_field="text"
)

then other codes..