Time Series Forecasting
Transformers
English
time-series
forecasting
passenger_occupancy
airport
weather
patchtst
transformer
cooling-load-prediction
multi-output
Instructions to use ritulk/patchtst-model-based-on-occupancy-weather-data-time-series with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ritulk/patchtst-model-based-on-occupancy-weather-data-time-series with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ritulk/patchtst-model-based-on-occupancy-weather-data-time-series", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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