Tabular Regression
RouteE-Powertrain
Joblib
ONNX
energy
transportation
mobility
vehicle-energy-consumption
routee
random-forest
ngboost
Instructions to use NatLabRockies/routee-powertrain-model-library with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- RouteE-Powertrain
How to use NatLabRockies/routee-powertrain-model-library with RouteE-Powertrain:
# pip install routee.powertrain import pandas as pd import routee.powertrain as pt from routee.powertrain.registry import HFRegistry registry = HFRegistry(repo_id="NatLabRockies/routee-powertrain-model-library") # find a vehicle: filter by make, model, year, powertrain type, features, ... pt.query_available_models(make="tesla", model="model 3", registry=registry) # load one by its id: "<make>/<vehicle_slug>/<year>/<config_slug>" model = pt.load_model("tesla/model_3_bev/2022/rf_c3326385", registry=registry) links = pd.DataFrame({ "distance": [0.1, 0.2], # miles "speed_mph": [30, 55], "grade_percent": [-2.0, 1.0], }) model.predict(links) - Notebooks
- Google Colab
- Kaggle