Instructions to use jirkoru/TemporalRegressionV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use jirkoru/TemporalRegressionV2 with Scikit-learn:
import joblib from skops.hub_utils import download download("jirkoru/TemporalRegressionV2", "path_to_folder") model = joblib.load( "model.pkl" ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
File size: 1,184 Bytes
e1487c4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | {
"sklearn": {
"columns": [
"time_first_funding",
"seed_funding",
"time_till_series_a",
"seed_n_rounds",
"angel_n_rounds",
"pre_seed_n_rounds"
],
"environment": [
"scikit-learn=1.1.3"
],
"example_input": {
"angel_n_rounds": [
0.0,
0.0,
0.0
],
"pre_seed_n_rounds": [
0.0,
0.0,
0.0
],
"seed_funding": [
1250000.0,
800000.0,
8000000.0
],
"seed_n_rounds": [
1.0,
3.0,
1.0
],
"time_first_funding": [
1270.0,
1856.0,
689.0
],
"time_till_series_a": [
1455.0,
1667.0,
1559.0
]
},
"model": {
"file": "model.pkl"
},
"model_format": "pickle",
"task": "tabular-classification"
}
} |