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license: apache-2.0
library_name: pytorch
pipeline_tag: time-series-forecasting
tags:
- time-series
- forecasting
- pytorch
- deployable
- edge-ai
- onnx
- streaming
- raspberry-pi
- transformer
- zero-shot
- iot
- real-time
- tiny-ml
- timesfm-alternative
- huggingface
metrics:
- mase
- smape
- mae
- crps
model-index:
- name: NanoForecast 500k
results:
- task:
type: time-series-forecasting
name: Time Series Forecasting
dataset:
name: ETTh1
type: ett
config: h1
metrics:
- type: mase
value: 3.342
name: MASE
- type: smape
value: 25.13
name: sMAPE (%)
- task:
type: time-series-forecasting
name: Time Series Forecasting
dataset:
name: ETTh2
type: ett
config: h2
metrics:
- type: mase
value: 3.707
name: MASE
- type: smape
value: 17.65
name: sMAPE (%)
- task:
type: time-series-forecasting
name: Time Series Forecasting
dataset:
name: ETTm1
type: ett
config: m1
metrics:
- type: mase
value: 3.578
name: MASE
- type: smape
value: 17.22
name: sMAPE (%)
- task:
type: time-series-forecasting
name: Time Series Forecasting
dataset:
name: Overall
type: multi-dataset
metrics:
- type: mase
value: 3.453
name: Overall MASE
- type: smape
value: 18.68
name: Overall sMAPE (%)
---
<h1 align="center">
🔮 NanoForecast 500k (v0.2)
<br>
<sub>Ultra-lightweight time series transformer</sub>
</h1>
<p align="center">
<b>1.6M params · 256 context · Streaming RNN · ONNX-ready</b>
<br>
<i>Runs on CPU, Raspberry Pi, and in the browser</i>
</p>
<p align="center">
<a href="https://huggingface.co/spaces/eulogik/nanoforecast"><img src="https://img.shields.io/badge/🤗%20Live%20Demo-Spaces-blueviolet"></a>
<a href="https://github.com/eulogik/NanoForecast"><img src="https://img.shields.io/badge/GitHub-eulogik%2FNanoForecast-181717?logo=github"></a>
<a href="https://pypi.org/project/nanoforecast/"><img src="https://img.shields.io/pypi/v/nanoforecast"></a>
<a href="https://eulogik.com"><img src="https://img.shields.io/badge/by-Eulogik-purple"></a>
</p>
<p align="center">
🚀 <b>New:</b> Try the improved <a href="https://huggingface.co/eulogik/nanoforecast-v03"><b>nanoforecast-v03</b></a> — 21% better MASE, 6.5M params, 512 context!
</p>
---
## 📦 Quick Start
```bash
pip install nanoforecast
```
```python
from nanoforecast import NanoForecast
model = NanoForecast.from_pretrained("eulogik/nanoforecast-500k")
```
## 🏆 Benchmarks
| Dataset | MASE | sMAPE (%) | MAE | CRPS |
|---|---:|---:|---:|---:|
| ETTh1 | 3.342 | 25.13 | 2.402 | 1.800 |
| ETTh2 | 3.707 | 17.65 | 3.212 | 2.518 |
| ETTm1 | 3.578 | 17.22 | 1.174 | 1.003 |
| exchange_rate | 7.306 | 1.63 | 0.010 | 0.009 |
| electricity | 1.536 | 5.65 | 189.748 | 187.256 |
| traffic | 1.246 | 44.80 | 0.006 | 0.005 |
| **Overall** | **3.453** | **18.68** | **32.759** | **32.099** |
> 🔥 For better accuracy, upgrade to [nanoforecast-v03](https://huggingface.co/eulogik/nanoforecast-v03) (MASE 2.73, **21% improvement**).
## 🔄 Streaming Inference (Unique to NanoForecast)
```python
result = model.predict(context, horizon=48, return_state=True)
state = result.pop("state")
for new_val in incoming_data_stream:
result = model.predict_step(new_val, state, horizon=48)
print(result["forecast"][0, :5])
```
Perfect for IoT, real-time dashboards, and live financial data.
## 📋 Model Details
| Attribute | Value |
|---|---|
| Profile | `d64-L8` |
| Parameters | 1,606,232 |
| Context | 256 |
| Horizon | 48 |
| Size | 6.4 MB (FP32), ~1.4 MB (ONNX) |
| Architecture | LongConv + DeltaNet RNN + Gated Router + MLP |
| Deploy targets | CPU, ARM, Raspberry Pi, Lambda, iOS, browser |
## 🎯 Try It in 1 Click
[](https://huggingface.co/spaces/eulogik/nanoforecast)
Upload a CSV → forecast + prediction intervals. No code. No GPU.
## 📚 All Variants
| Model | Params | Context | MASE | Best For |
|---|---|---|---|---|
| [nanoforecast-200k](https://huggingface.co/eulogik/nanoforecast-200k) | 676K | 256 | ~4-11 | Extreme edge / RPi Zero |
| **nanoforecast-500k** (you are here) | **1.6M** | **256** | **3.45** | General purpose |
| [nanoforecast-v03](https://huggingface.co/eulogik/nanoforecast-v03) | **6.5M** | **512** | **2.73** | Max accuracy |
## ⚡ Deploy
```bash
# FastAPI
pip install nanoforecast fastapi uvicorn python-multipart
python3 deploy/fastapi_server.py
# ONNX
pip install "nanoforecast[onnx]"
python3 -m nanoforecast.export.onnx_export --checkpoint <dir> --output nanoforecast.onnx
```
## ❤️ Built by Eulogik
[](https://eulogik.com)
**Eulogik** — deployable AI for the real world.
Star the repo ⭐ on [GitHub](https://github.com/eulogik/NanoForecast)!
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