The qm8 dataset is a collection of molecular structures and their associated properties specifically designed for benchmarking quantum machine learning models in the field of quantum chemistry. It contains 134,000 small organic molecules and their energies, providing valuable data for training machine learning algorithms to predict molecular properties efficiently. This dataset plays a crucial role in understanding how quantum machine learning can be applied to solve complex problems in quantum chemistry.
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