---
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.