Introducing the Synthetic Data Generator - Build Datasets with Natural Language

Source: HuggingFace Date: 2024-12-16 URL: https://huggingface.co/blog/synthetic-data-generator

Summary

Tool release: HuggingFace’s no-code Synthetic Data Generator, a 3-step UI for generating classification and chat/SFT datasets using LLMs. Generates ~50 samples/min (text classification) or ~20/min (chat) using the free HF API with Llama 3.1-8B. Backend is distilabel; integrates with Argilla for review and AutoTrain for downstream model training. Apache 2.0, locally deployable. No benchmarks.

Implications

Thread: HF as open-source ML hub. This is HF closing the loop on its platform: generate synthetic data → review in Argilla → train in AutoTrain, all within the HF ecosystem without writing code. The distilabel backend makes the pipelines reproducible and inspectable. The no-code framing extends the target user beyond ML engineers to domain experts who need task-specific datasets. Roadmap items (RAG datasets, LLM-based evaluations) suggest this becomes a general data factory product — watch for those additions as they’d significantly expand the use case surface.