Show HN: 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: 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!

Summary

Hyperparam.app is an open-source platform that provides a user-friendly interface for managing and optimizing hyperparameters in machine learning models. The platform supports a wide range of machine learning frameworks and offers features such as automatic experiment tracking, visualization tools, and collaborative model development.

Story

Show HN: Hyperparam: OSS tools for exploring datasets locally in the browser