This repo contains notebooks for Pytorch Serving Workshop.
Note: We do not need a GPU runtime
If you came to this repo, during a workshop visit this custom jupyter hub with all the dependencies already set up.
Otherwise, consider using
There are five notebooks.
a. 00_prepare_dataset.ipynb
Notebook that prepares the e-comeerce dataset and saves it.
b. 01_train.ipynb
Trains a DistilBert model
c. 02_inference_review.ipynb
Notebook that shows how to use the HuggingFace ecosystem. Also shows how to use the trained model from previous notebook.
d. 03_optimizing_model.ipynb
Notebook that shows impact of Quantization and TorschScript
e. 04_packaging.ipynb
Notebook that shows how to use TorchServe to serve models
This repro uses HuggingFace transformers and dataset pacakge.
The dataset used is Amazon Berkeley Objects (ABO) Dataset created by Amazon and UC Berkeley. For more reference, refer to this paper
For help or feedback, please reach out to :