metadata
license: apache-2.0
library_name: PyTorch
tags:
- time-series
- zero-shot-forecasting
- xlstm
- forecasting
pipeline_tag: time-series-forecasting
ForecastAgent 1.0
ForecastAgent 1.0 is a zero-shot and fine-tuned time series forecasting foundation model powered by an xLSTM backbone architecture.
Model Details
- Backbone: xLSTM (based on temporal/variate mixers)
- Parameters: ~82.5M
- Task: Zero-Shot Probabilistic Time Series Forecasting
- Output: 9 Quantiles (10% to 90% percentiles)
- License: Apache-2.0
Usage
You can load and use this model directly using the forecast-agent-sdk Python SDK:
from forecastagent import ForecastAgent
# Load the model from Hugging Face
agent = ForecastAgent.from_pretrained("shinydatatech/forecastagent-v1.0")
# Input target history (e.g., hourly electricity consumption)
history = [10.2, 11.5, 12.1, 11.8, 13.0, 14.5, 15.2, 14.8, 13.9, 13.1]
# Predict 24 steps forward
results = agent.predict(
target=history,
prediction_length=24,
freq="h"
)
print("Median Forecast:", results["median"])
print("10th percentile:", results["lower"])
print("90th percentile:", results["upper"])
Developers & Licensing
Developed by ShinyDataTech (shinydatatech@gmail.com). Licensed under Apache 2.0.