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, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": "predictive-maintenance", | |
| "format": "fp16-streaming", | |
| "note": "load order is smallest-first for progressive/streaming load", | |
| "files": [ | |
| { | |
| "file": "cmapss_FD001_fp16.safetensors", | |
| "source": "cmapss_FD001.safetensors", | |
| "dtype": "fp16", | |
| "bytes": 251818, | |
| "approx_mb": 0.24 | |
| }, | |
| { | |
| "file": "cmapss_FD002_fp16.safetensors", | |
| "source": "cmapss_FD002.safetensors", | |
| "dtype": "fp16", | |
| "bytes": 251818, | |
| "approx_mb": 0.24 | |
| }, | |
| { | |
| "file": "cmapss_FD003_fp16.safetensors", | |
| "source": "cmapss_FD003.safetensors", | |
| "dtype": "fp16", | |
| "bytes": 251818, | |
| "approx_mb": 0.24 | |
| }, | |
| { | |
| "file": "cmapss_FD004_fp16.safetensors", | |
| "source": "cmapss_FD004.safetensors", | |
| "dtype": "fp16", | |
| "bytes": 251818, | |
| "approx_mb": 0.24 | |
| }, | |
| { | |
| "file": "model_fp16.safetensors", | |
| "source": "model.safetensors", | |
| "dtype": "fp16", | |
| "bytes": 251818, | |
| "approx_mb": 0.24 | |
| }, | |
| { | |
| "file": "cwru_fp16.safetensors", | |
| "source": "cwru.safetensors", | |
| "dtype": "fp16", | |
| "bytes": 268100, | |
| "approx_mb": 0.256 | |
| } | |
| ] | |
| } |