Update README.md

README.md

@@ -7,4 +7,58 @@ sdk: docker
 pinned: false
 ---
 
+```
+import mlflow
+import numpy as np
+from sklearn.linear_model import LinearRegression
+from sklearn.metrics import mean_squared_error
+from sklearn.datasets import make_regression
+from sklearn.model_selection import train_test_split
+
+# Set the tracking URI to point to your MLflow server
+mlflow.set_tracking_uri("https://subhrajit-mohanty-mlflow.hf.space")
+
+# Create an experiment or use an existing one
+experiment_name = "file-store-experiment"
+try:
+    experiment_id = mlflow.create_experiment(experiment_name)
+except:
+    experiment_id = mlflow.get_experiment_by_name(experiment_name).experiment_id
+
+# Set the experiment
+mlflow.set_experiment(experiment_name)
+
+# Create a simple dataset
+X, y = make_regression(n_samples=100, n_features=5, noise=0.1, random_state=42)
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+# Start an MLflow run
+with mlflow.start_run(run_name="metrics_only_example"):
+    # Log parameters
+    mlflow.log_param("model_type", "LinearRegression")
+    mlflow.log_param("n_features", X.shape[1])
+    mlflow.log_param("n_samples", X.shape[0])
+    
+    # Train the model
+    model = LinearRegression()
+    model.fit(X_train, y_train)
+    
+    # Make predictions and evaluate
+    y_pred = model.predict(X_test)
+    mse = mean_squared_error(y_test, y_pred)
+    
+    # Log metrics only (avoiding artifact storage)
+    mlflow.log_metric("mse", mse)
+    mlflow.log_metric("r2_score", model.score(X_test, y_test))
+    
+    # Log coefficients as parameters instead of storing the model
+    for i, coef in enumerate(model.coef_):
+        mlflow.log_param(f"coef_{i}", coef)
+    mlflow.log_param("intercept", model.intercept_)
+    
+    print(f"Run completed with MSE: {mse:.4f}")
+    print(f"Metrics and parameters have been logged to MLflow")
+    print(f"Run ID: {mlflow.active_run().info.run_id}")
+```
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference