| import gradio as gr | |
| with gr.Blocks() as app: | |
| gr.Markdown( | |
| """ | |
| Synthetic data is artificially generated information that mimics real-world data. It allows overcoming data limitations by expanding or enhancing datasets. | |
| Introducing the Synthetic Data Generator, a user-friendly application that takes a no-code approach to creating custom datasets with Large Language Models (LLMs). The best part: A simple step-by-step process, making dataset creation a non-technical breeze, allowing anyone to create datasets and models in minutes and without any code. | |
| The synthetic data generator takes your custom prompt and returns a dataset for your use case, using a synthetic data pipeline. In the background this is powered by [distilabel](https://distilabel.argilla.io/latest/) and the [free Hugging Face text-generation API](https://huggingface.co/docs/api-inference/en/index) but we don’t need to worry about these complexities and we can focus on using the UI. | |
| - Read more in [our announcement blog post](https://huggingface.co/blog/synthetic-data-generator) | |
| - Find the library on [GitHub](https://github.com/argilla-io/synthetic-data-generator) | |
| """ | |
| ) | |