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Shortened component description (qiskit-torch-module) #139

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5 changes: 1 addition & 4 deletions _components/qiskit-torch-module.md
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Expand Up @@ -14,7 +14,4 @@ maintainers:

The qiskit-torch-module is a Qiskit-based simulation and training framework for variational quantum
circuits with a native PyTorch interface, designed for fast prototyping of quantum neural networks
on single-CPU machines. It provides efficient multi‑observable evaluation, batch‑parallelized
expectation and gradient computation, and flexible automatic differentiation for hybrid
classical–quantum models. Compared to qiskit‑machine‑learning, it achieves up to two orders of
magnitude lower runtimes with minimal code changes to existing Qiskit workflows.
on single-CPU machines.