| from huggingface_hub import hf_hub_url, cached_download | |
| import joblib | |
| import pandas as pd | |
| REPO_ID = "julien-c/wine-quality" | |
| FILENAME = "sklearn_model.joblib" | |
| model = joblib.load(cached_download( | |
| hf_hub_url(REPO_ID, FILENAME) | |
| )) | |
| # model is a `sklearn.pipeline.Pipeline` | |
| #GET SAMPLE DATA | |
| data_file = cached_download( | |
| hf_hub_url(REPO_ID, "winequality-red.csv") | |
| ) | |
| df = pd.read_csv(dataset) | |
| X = df.drop(["Target"], axis=1) | |
| Y = df["Target"] | |
| print(X[:3]) | |
| #GET PREDICTIONS | |
| labels = model.predict(X[:3]) | |
| #EVALUATE | |
| model.score(X, Y) | |