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        "description": "# PyTorchWrapper\n\nPyTorchWrapper is a library that provides a systematic and extensible way to build, train, evaluate, and tune deep learning models\nusing PyTorch. It also provides several ready to use modules and functions for fast model development.\n\n## Installation\n\n### From PyPI\n```bash\npip install pytorch-wrapper\n```\n\n### From Source\n\n```bash\ngit clone https://github.com/jkoutsikakis/pytorch-wrapper.git\ncd pytorch-wrapper\npip install .\n```\n\n## Docs & Examples\n\nThe docs can be found [here](https://pytorch-wrapper.readthedocs.io/en/latest/).\n\nThere are also the following examples in notebook format:\n\n1. [Two Spiral Task](examples/1_two_spiral_task.ipynb)\n2. [Image Classification Task](examples/2_image_classification_task.ipynb)\n3. [Tuning Image Classifier](examples/3_tuning_image_classifier.ipynb)\n4. [Text Classification Task](examples/4_text_classification_task.ipynb)\n5. [Sequence Classification Task](examples/5_sequence_classification_task.ipynb)\n6. [Custom Callback](examples/6_custom_callback.ipynb)\n7. [Custom Loss Wrapper](examples/7_custom_loss_wrapper.ipynb)\n8. [Custom Evaluator](examples/8_custom_evaluator.ipynb)",
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