Add model card (README.md)

README.md

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+---
+datasets:
+- dummy-data
+library_name: scikit-learn
+license: apache-2.0
+metrics:
+- r2_score
+model_name: Linear Regression Model V2
+tags:
+- linear-regression
+- example
+- scikit-learn
+---
+
+# Linear Regression Model V2
+
+This is a simple linear regression model trained on a dummy dataset.
+
+## Model Description
+
+This model predicts a `target` variable based on two features, `feature1` and `feature2`. It's a basic example to demonstrate model saving and uploading to Hugging Face Hub.
+
+## Training Data
+
+The model was trained on a small, synthetic dataset:
+
+feature1: [1, 2, 3, 4, 5]
+feature2: [5, 4, 3, 2, 1]
+target: [2, 4, 6, 8, 10]
+
+
+## Usage
+
+To use this model, you can load it using `joblib` and make predictions:
+
+
+import joblib
+from huggingface_hub import hf_hub_download
+
+# Download the model file
+model_path = hf_hub_download(repo_id="Ashpgsem/rdmai", filename="linear_regression_modelV2.joblib")
+
+# Load the model
+model = joblib.load(model_path)
+
+# Make a prediction
+import pandas as pd
+new_data = pd.DataFrame([{'feature1': 6, 'feature2': 0}])
+prediction = model.predict(new_data)
+print(f"Prediction: {prediction}")
+
+
+## Evaluation
+
+Since this is a dummy model, formal evaluation metrics are not extensively provided. The model perfectly fits the provided dummy data.
+
+## Limitations
+
+This model is for demonstration purposes only and should not be used for real-world applications without proper training on relevant data and thorough evaluation.