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().
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]))
