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README.md

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+
+---
+tags:
+- sklearn
+- linear-regression
+- example
+---
+# Linear Regression Model for Ashpgsem
+
+This is a simple linear regression model trained on dummy data.
+
+## Model Description
+
+This model is a `sklearn.linear_model.LinearRegression` instance. It was trained to predict a target variable `y_train` based on two features, `feature1` and `feature2`.
+
+## Training Data
+
+The model was trained on the following dummy data:
+
+**Features (X_train):**
+
+|   feature1 |   feature2 |
+|-----------:|-----------:|
+|          1 |          5 |
+|          2 |          4 |
+|          3 |          3 |
+|          4 |          2 |
+|          5 |          1 |
+
+
+**Target (y_train):**
+
+|   0 |
+|----:|
+|   2 |
+|   4 |
+|   5 |
+|   4 |
+|   5 |
+
+
+## Training Procedure
+
+The model was trained using the default parameters of `sklearn.linear_model.LinearRegression`.
+
+## Usage
+
+This model can be loaded using `skops.io`:
+
+
+import skops.io as sio
+from huggingface_hub import hf_hub_download
+
+model_path = hf_hub_download(repo_id="Ashpgsem/rdmai_v2", filename="linear_regression_model.skops")
+model = sio.load(model_path)
+
+# Example prediction
+import pandas as pd
+new_data = pd.DataFrame({'feature1': [6, 7], 'feature2': [0, -1]})
+predictions = model.predict(new_data)
+print(predictions)
+
+
+## Limitations
+
+This model is trained on very limited dummy data and should not be used for any real-world applications. It serves purely as an example for demonstrating model saving and sharing on Hugging Face Hub.