Update README.md
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README.md
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@@ -71,9 +71,9 @@ For your screening, load the model, i.e. the **Activity Predictor** into your py
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from src.prediction_pipeline load ActivityPredictor
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# Define inputs
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query_smiles = ["C1CCCCC1", "C1CCCCC1", "C1CCCCC1", "C1CCCCC1"]
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support_actives_smiles = ["C1CCCCC1", "C1CCCCC1"]
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support_inactives_smiles = ["C1CCCCC1", "C1CCCCC1"]
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# Make predictions
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predictions = predictor.predict(query_smiles, support_actives_smiles support_inactives_smiles)
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from src.prediction_pipeline load ActivityPredictor
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# Define inputs
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query_smiles = ["C1CCCCC1", "C1CCCCC1", "C1CCCCC1", "C1CCCCC1"] # Replace with your data
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support_actives_smiles = ["C1CCCCC1", "C1CCCCC1"] # Replace with your data
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support_inactives_smiles = ["C1CCCCC1", "C1CCCCC1"] # Replace with your data
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# Make predictions
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predictions = predictor.predict(query_smiles, support_actives_smiles support_inactives_smiles)
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