Entrepreneur Readiness — Ridge (All Rows)
This model is a Ridge regressor trained on all rows of
Lazabriellholland/entrepreneur-readiness-datasett.
Each row is converted to a string of key:value pairs (joined by |), embedded with
sentence-transformers/all-MiniLM-L6-v2, then fit with Ridge().
Quick use (Python)
from huggingface_hub import hf_hub_download import joblib, json from sentence_transformers import SentenceTransformer
REPO = "Lazabriellholland/entrepreneur-readiness-ridge-allrows" reg_path = hf_hub_download(REPO, "ridge_model.pkl") meta_path = hf_hub_download(REPO, "ridge_meta.json")
reg = joblib.load(reg_path) meta = json.load(open(meta_path)) embedder = SentenceTransformer(meta["hf_embedding_model"]) cols = meta["feature_columns"]
row = {c: 0 for c in cols} # replace with your values text = " | ".join(f"{c}:{row[c]}" for c in cols) X = embedder.encode([text], convert_to_numpy=True) print(float(reg.predict(X)[0]))
Model files
ridge_model.pkl— trained regressor (joblib)ridge_meta.json— metadata (hf_embedding_model,feature_columns, etc.)
Notes
- Final model is trained on all available rows of the dataset (no holdout).
- For evaluation, run CV or a holdout split before the final all-rows retrain.