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Update README.md
Co-authored-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu> Signed-off-by: HydrogenSulfate <490868991@qq.com>
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### Highlighted features
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- **interfaced with multiple backends**, including TensorFlow, PyTorch, JAX and Paddle, the most popular deep learning frameworks, making the training process highly automatic and efficient.
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- **interfaced with multiple backends**, including TensorFlow, PyTorch, JAX, and Paddle, the most popular deep learning frameworks, making the training process highly automatic and efficient.
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- **interfaced with high-performance classical MD and quantum (path-integral) MD packages**, including LAMMPS, i-PI, AMBER, CP2K, GROMACS, OpenMM, and ABACUS.
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- **implements the Deep Potential series models**, which have been successfully applied to finite and extended systems, including organic molecules, metals, semiconductors, insulators, etc.
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- **implements MPI and GPU supports**, making it highly efficient for high-performance parallel and distributed computing.

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