individual_steps/install_and_preprocess.py

import os
os.system("pip install sentencepiece")

from datasets import load_dataset
from transformers import T5Tokenizer

# Load dataset
dataset = load_dataset('json', data_files='dataset.json')

# Load T5 tokenizer
tokenizer = T5Tokenizer.from_pretrained('t5-small')

# Preprocess function
def preprocess_function(examples):
    inputs = ["question: " + q for q in examples['input']]
    targets = examples['response']
    model_inputs = tokenizer(inputs, max_length=128, truncation=True, padding='max_length')
    labels = tokenizer(targets, max_length=32, truncation=True, padding='max_length')
    model_inputs['labels'] = labels['input_ids']
    return model_inputs

# Apply preprocessing
processed_dataset = dataset.map(preprocess_function, batched=True)

# Save processed dataset
processed_dataset.save_to_disk('processed_dataset')

print("Dataset preprocessed and saved to 'processed_dataset'")