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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.
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