Time Series Forecasting
Transformers
Safetensors
PyTorch
telos
feature-extraction
time-series
probabilistic-forecasting
jepa
world-model
foundation-model
custom_code
Instructions to use magilabsco/Telos-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magilabsco/Telos-Small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("magilabsco/Telos-Small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from magilabsco/Telos-Small: direct link, hf CLI and curl.
- Browser
- Download file 565 Bytes
-
https://huggingface.co/magilabsco/Telos-Small/resolve/main/__init__.py
- Command line
-
hf download hf://magilabsco/Telos-Small/__init__.py
-
curl -L -o __init__.py https://huggingface.co/magilabsco/Telos-Small/resolve/main/__init__.py
565 Bytes
| """Telos (`Telos-Small`, 50.1M Parameters): Standalone Time-Series JEPA Foundation Model.""" | |
| from .configuration_telos import QUANTILE_KNOTS_21, TelosConfig | |
| from .modeling_telos import ( | |
| ROLE_KNOWN_COV, | |
| ROLE_PAST_COV, | |
| ROLE_TARGET, | |
| TelosForForecasting, | |
| TelosModel, | |
| load_telos_checkpoint, | |
| save_telos_checkpoint, | |
| ) | |
| __all__ = [ | |
| "QUANTILE_KNOTS_21", | |
| "ROLE_KNOWN_COV", | |
| "ROLE_PAST_COV", | |
| "ROLE_TARGET", | |
| "TelosConfig", | |
| "TelosForForecasting", | |
| "TelosModel", | |
| "load_telos_checkpoint", | |
| "save_telos_checkpoint", | |
| ] | |