TutorialsΒΆ
The following are examples and notebooks on how to use skorch.
- Basic Usage - Explores the basics of the skorch API. Run in Google Colab π»
- MNIST with scikit-learn and skorch - Define and train a simple neural network with PyTorch and use it with skorch. Run in Google Colab π»
- Benchmarks skorch vs pure PyTorch - Compares the performance of skorch and using pure PyTorch on MNIST.
- Transfer Learning with skorch - Train a neural network using transfer learning with skorch. Run in Google Colab π»
- Image Segmentation with UNets - Use transfer learning to train a UNet model for image segmentation.
- Using skorch with Dask - Using Dask to parallelize grid search across GPUs.
- World level language modeling RNN - Uses skorch to train a language model.
- Seq2Seq Translation using skorch - Translation with a seqeuence to sequence network.
- Advanced Usage - Dives deep into the inner works of skorch. Run in Google Colab π»
- Gaussian Processes - Train Gaussian Processes with the help of GPyTorch. Run in Google Colab π»
- Hugging Face Finetunging - Fine-tune a BERT model for text classification with the Hugging Face transformers library and skorch. Run in Google Colab π»
- Hugging Face Vision Transformer - Show how to fine-tune a vision transformer model for a classification task using the Hugging Face transformers library and skorch. Run in Google Colab π»
- SkorchDoctor - Diagnosing problems in training your neural net Run in Google Colab π»
- Classifying with LLMs - Using (Large) Language Models as zero-shot and few-shot classifiers Run in Google Colab π»