Hyperparam Product

What is Hyperparam?

Hyperparam is a new type of data app that can run entirely in the browser. Built from the ground up to handle modern data formats like parquet, it scales to billions of rows while remaining blazing fast and interactive.

Unlike traditional Python-centric data tools, Hyperparam embraces frontend-first development, bringing powerful data exploration capabilities directly to your browser. Whether you're working with small datasets locally or massive datasets in the cloud, Hyperparam adapts to your needs.

Key Features

Model-Assisted Transformation

Hyperparam integrates large language models to help you understand and transform your data. Use natural language prompts to generate new columns, extract structured fields from unstructured text, clean existing data, or create quality scores. This makes dataset preparation intuitive and powerful.

Browser-Native Performance

Read and analyze parquet files directly in the browser with on-demand row retrieval. No need to download entire datasets or wait for slow data transfers. Work with massive files while maintaining instant interactivity.

Flexible Data Operations

Filter, sort, sample, and export your data with ease. Create workspaces to iterate on smaller samples before applying transformations to full datasets. Export filtered and transformed data in parquet format, ready for training or further analysis.

Natural Language Search

Find datasets using conversational queries. Search across Hugging Face and other sources without browsing through endless file listings. Get relevant results based on your domain-specific needs.

Use Cases

  • Dataset Discovery: Find relevant datasets using natural language queries
  • Quality Filtering: Score and filter low-quality examples from training data
  • Field Extraction: Extract structured fields from unstructured text records
  • Categorization: Classify and organize data based on content patterns
  • Data Cleaning: Transform and normalize data for downstream tasks

Learn More

Ready to see Hyperparam in action? Check out our workflow examples to learn how to use Hyperparam for common machine learning data tasks.