Instructions to use THEORACLEEEE/polymarket-logreg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use THEORACLEEEE/polymarket-logreg with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("THEORACLEEEE/polymarket-logreg", "sklearn_model.joblib") ) # 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: 858 Bytes
74a7d38 | 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 | {
"task": "classification",
"target": "price_up_7d",
"horizonDays": 7,
"features": [
"p",
"mom1",
"mom7",
"rev",
"absdev"
],
"mean": [
0.15584628258444164,
-0.0002917469655475525,
-0.0032803867870304813,
0.3441537174155534,
0.38510929100314234
],
"scale": [
0.2191645307830682,
0.023693971118216424,
0.05043064578101504,
0.219164530783067,
0.1347802164539187
],
"coef": [
0.11196571203683481,
-0.08715199356646906,
-0.11682737891742023,
-0.11196571203684959,
-0.0847639025228879
],
"intercept": -0.7173628634460989,
"version": "logreg.updown.v1",
"metrics": {
"auc": 0.65507,
"accuracy": 0.67072,
"dirAcc": 0.6018,
"upRate": 0.33114,
"n_train": 23661,
"n_test": 5916,
"trained_at": "2026-06-22T02:07:59.810666+00:00"
}
} |