From e0033e93e58284e4dd9301fe10286995ad5f5bc1 Mon Sep 17 00:00:00 2001 From: gautamkishore Date: Mon, 29 Jun 2026 11:23:09 +0530 Subject: [PATCH] Add NanoForecast to Libraries table NanoForecast is a lightweight time series foundation model for streaming inference and edge deployment, with ONNX export and HF Hub integration. --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 3d6f36d..88e3a22 100644 --- a/README.md +++ b/README.md @@ -26,6 +26,7 @@ The following list is by no means exhaustive, feel free to edit the list (will p | [HMMLearn](https://github.com/hmmlearn/hmmlearn) | Hidden Markov Models with scikit-learn compatible API | | [khiva-python](https://github.com/shapelets/khiva-python) | A Time Series library with accelerated analytics on GPUS, it provides feature extraction and motif discovery among other functionalities.| | [matrixprofile-ts](https://github.com/target/matrixprofile-ts) | Python implementation of the Matrix Profile algorithm which offers anomaly detection and pattern (or “motif”) discovery at the same time. | +| [NanoForecast](https://github.com/eulogik/NanoForecast) | Lightweight time series foundation model (200K-6.5M params) with streaming RNN inference, ONNX edge deployment, and HuggingFace Hub integration. Runs on CPU and Raspberry Pi. | | [Nitime](https://github.com/nipy/nitime) | Timeseries analysis for neuroscience data | | [Orbit](https://github.com/uber/orbit) | Orbit is a Python package for Bayesian time series forecasting and inference | | [Pandas TA](https://github.com/twopirllc/pandas-ta) | An easy to use Python 3 Pandas Extension with 130+ Technical Analysis Indicators |