Hyperparam: OSS tools for exploring datasets locally in the browser
For the last year I’ve been developing Hyperparam — a collection of small, fast, dependency-free open-source libraries designed for data scientists and ML engineers to actually look at their data. - Hyparquet: Read any Parquet file in browser/node.js - Icebird: Explore Iceberg tables without needing Spark/Presto - HighTable: Virtual scrolling of millions of rows - Hyparquet-Writer: Export Parquet easily from JS - Hyllama: Read llama.cpp .gguf LLM metadata efficiently CLI for viewing local files: npx hyperparam dataset.parquet Example dataset on Hugging Face Space:…
In plain words
Hyperparam is a collection of open-source libraries that lets data scientists and ML engineers explore datasets directly in the browser without cloud uploads or backend servers. It includes tools for reading Parquet files, exploring Iceberg tables, handling millions of rows with virtual scrolling, and accessing LLM metadata. The lightweight, dependency-free libraries work locally in the browser or Node.js, with a CLI for quick file inspection.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
For the last year I’ve been developing Hyperparam — a collection of small, fast, dependency-free open-source libraries designed for data scientists and ML engineers to actually look at their data. - Hyparquet: Read any Parquet file in browser/node.js - Icebird: Explore Iceberg tables without needing Spark/Presto - HighTable: Virtual scrolling of millions of rows - Hyparquet-Writer: Export Parquet easily from JS - Hyllama: Read llama.cpp .gguf LLM metadata efficiently CLI for viewing local files: npx hyperparam dataset.parquet Example dataset on Hugging Face Space: https://huggingface.co/spaces/hyperparam/hyperparam?url=http... No cloud uploads. No backend servers. A better way to build frontend data applications. GitHub: https://github.com/hyparam Feedback and PRs welcome!
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