File size: 1,307 Bytes
ea3c921
 
 
 
 
 
 
 
 
 
 
 
 
85c62dc
ea3c921
 
85c62dc
ea3c921
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
---
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:

```python
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.