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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Open Chemistry JupyterLab ChemML calculations
Step1:  Start by finding structures using online databases (or cached local results). This uses an InChI for a known structure that will be added if not already present using Open Babel.
Step2:  Set up the calculation, by specifying the name of the Docker image that will be used, and by providing input parameters that are known to the specific image
Step3:  Predict Properties from ML Model
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Python Code:
import openchemistry as oc
Explanation: Open Chemistry JupyterLab ChemML calculations
End of explanation
mol = oc.find_structure('InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H')
mol.structure.show()
Explanation: Start by finding structures using online databases (or cached local results). This uses an InChI for a known structure that will be added if not already present using Open Babel.
End of explanation
image_name = 'openchemistry/chemml:0.6.0'
input_parameters = {}
Explanation: Set up the calculation, by specifying the name of the Docker image that will be used, and by providing input parameters that are known to the specific image
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result = mol.calculate(image_name, input_parameters)
result.properties.show()
Explanation: Predict Properties from ML Model
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