Time Series Forecasting
Transformers
Safetensors
fela-pdm
feature-extraction
fela
fourier-neural-operator
fno
cpu
on-device
predictive-maintenance
time-series
anomaly-detection
custom_code
Instructions to use lowdown-labs/fela-pdm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lowdown-labs/fela-pdm with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lowdown-labs/fela-pdm", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99a6d7abca1b021b1cacf72e61ff8a951dfc06905ee24b1e59279bd7b64515aa
- Size of remote file:
- 501 kB
- SHA256:
- c3705ce4f528830dcfdfceb897f94a48e2e11e4fdab4d1db8f739047af08f91c
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