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bakshinghampalace/timesfm-2.5-200m-onnx

AI model by bakshinghampalace

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[](https://www.npmjs.com/package/forecast-web) [](https://vatsalbakshi.com/forecast-web/) [](https://github.com/forge-veil/forecast-web) [](#license) ONNX exports of Google Research's TimesFM 2.5 (200M), built to run time series forecasting entirely in the browser on WebGPU or WebAssembly. They are the default TimesFM weights of the forecast-web npm package, a browser forecasting library with a choice of models. Give it a history of up to 512 points and get back a forecast up to 128 steps ahead, with a median and nine quantile bands. No server, no training, no API key. Try the live demo: stocks, live weather, Wikipedia traffic and classic seasonal data, forecast and backtested in your browser. React: The library picks the format and backend automatically, runs inference in a Web Worker, handles missing values, and reproduces the official forecast post-processing. See the package README for all options. config.json lists every file's size and SHA-256, plus the pinned source revision. The library keys its browser cache by those hashes,…

bakshinghampalace/timesfm-2.5-200m-onnx on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. TimesFM 2.5 200M for the browser
  2. Quick start
  3. Files
  4. Why a custom fp16 format
  5. Why 8-bit is WASM only
  6. Accuracy
  7. Speed
  8. The graph
  9. Running the raw graph
  10. How these files were made
  11. Limitations
  12. Citation

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Model overview

bakshinghampalace/timesfm-2.5-200m-onnx is a task-unspecified model repository published by bakshinghampalace on Hugging Face. A library was not reported.

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License
apache-2.0
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Created
2026-10-12T06:38:46.000Z
Last modified
2026-10-12T06:38:47.000Z

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