README.md

---
license: mit
language:
- en
base_model: ibm-granite/granite-timeseries-patchtst
tags:
- time-series
- forecasting
- patchtst
- electricity
- eirgrid
- energy
metrics:
- mse
- mae
library_name: transformers
pipeline_tag: time-series-forecasting
---
# PatchTST EirGrid Forecaster ⚡

This is a **PatchTST** model fine-tuned on **EirGrid (Irish Grid) System Data** to forecast electricity demand.

## Model Details
- **Architecture:** PatchTST (Transformer-based Time Series)
- **Base Model:** `ibm-granite/granite-timeseries-patchtst`
- **Task:** Long-term Forecasting (96-hour horizon)
- **Input:** 512 hours of historical load data.
- **Output:** 96 hours of future load forecast.

## Usage
```python
from transformers import PatchTSTForPrediction

# Load the model
model = PatchTSTForPrediction.from_pretrained("Priyansu19/patchtst-eirgrid-forecaster")