The dataset exploration tool for improving your AI data
Work with large datasets in your browser using fast, human-guided workflows.
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The Swiss Army knife for your data
Hyperparam is a fast, browser-native dataset exploration tool designed to help you find, filter, transform and improve large datasets with ease. Here are just a few of the workflows you can run with Hyperparam.
Fast dataset discovery: find datasets via chat
Instantly discover relevant datasets using natural-language queries:
- Open the chat.
- Type what you're looking for in plain English.
- Hyperparam immediately fetches matching datasets from Hugging Face.
- Open any result directly in the data viewer.
- The dataset loads with all columns and metadata.
Expected results: quick discovery, direct access, preserved context.
Data quality filtering: remove sycophantic responses
Filter out low-quality, overly agreeable responses from large chat log datasets:
- Load your dataset (e.g. a 200K-row chat log)
- Use the chat to request, "Add a sycophancy score for each row."
- Apply filter: sycophancy_score < 0.2.
- This keeps only non-pandering responses.
- Export the filtered dataset.
Expected results: New sycophancy_score column, filtered dataset, output as cleaned Parquet file.
Data transformation: categorize system prompts
Use the AI chat to categorize system prompts:
- Load your conversation dataset.
- In the chat, query, "Look for conversation datasets with at least 100,000 examples."
- Examine the data in the system_prompt column.
- In the chat, request, "Create a new column that categorizes the system prompt."
- Verify category assignments and export the categorized dataset.
Expected results: New categorical column, pattern insights, enhanced metadata.
Complete workflow: patient data extraction and filtering
Extract structured fields from raw patient text and filter the rows you need:
- In chat, ask, "Find me anonymized patient data with medical charting."
- Open a dataset and inspect the input_text column for clinical details.
- Request structured extraction (age, diagnosis, symptoms, comorbidities, treatments, outcome).
- Apply filters to isolate the rows that matter and export the results.
Expected results: Extracted columns, filtered sample, final sample of remaining rows with selected columns only.
Features built for large-scale dataset workflows
Powerful performance
Load tens of thousands of rows of data in a fraction of the time it takes traditional tools.
AI-assisted data exploration
Use Hyperparam's AI chat to view, sort, score, filter, tag, and transform your data. Add or remove columns, categorize data, and export clean output instantly.
Browser-first security benefits
Work with your data locally in the browser by default: nothing leaves your machine unless you choose to upload files to your account. Exported datasets are saved securely to your account.
Supported formats
Effortlessly load multi-gigabyte Parquet, JSONL, or CSV files in milliseconds.
Export options
Finished transforming your data? Export it as a Parquet, JSONL, or CSV file to seamlessly continue with your workflow.