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        "description": "# TorchWrapper\n\nA wrapper class for a PyTorhc Model using fit and predict functions that are\nfamiliar to those who use Keras and Sklearn.\n\nReduces the need to write fit and evaluation functions for basic models.\n\n## Quick Start\n\n```python\n# import the module\nfrom torchwrapper import Wrapper\n\n# create your module, optimizer, and criterion function\nmodel = Model()\noptimizer = torch.optim.Adam(model.parameters())\ncriterion = torch.nn.MSELos()\n\n# wrap the model\nmodel = Wrapper(model)\n\n# train the network\nmodel.fit(dataloader, optimizer, criterion, epochs=50)\n\n```\n\nWith a trained model, you can predict using a PyTorch dataloader:\n\n```python\npreds = model.predict(dataloader)\n```\n\nThis will return a numpy array of the predictions.",
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        "license": "MIT",
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