| # my_text_to_text_dataset.py | |
| from datasets import Dataset | |
| from text_generation import YourTextGenerationModel | |
| def generate_text_to_text_data(): | |
| # Your data generation logic here | |
| prompts = ["Tell a story about", "Describe a scene with", "Explain the concept of"] | |
| your_model = YourTextGenerationModel() | |
| generated_texts = [your_model.generate_text(prompt) for prompt in prompts] | |
| data = { | |
| "input_text": prompts, | |
| "target_text": generated_texts | |
| } | |
| return data | |
| def create_text_to_text_huggingface_dataset(): | |
| data = generate_text_to_text_data() | |
| dataset = Dataset.from_dict(data) | |
| return dataset | |
| if __name__ == "__main__": | |
| text_to_text_huggingface_dataset = create_text_to_text_huggingface_dataset() | |
| text_to_text_huggingface_dataset.save_to_disk("my_text_to_text_dataset") |