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text_classification

README.md

Text Classfication using TorchServe's default text_classifier handler

This is an example to create a text classification dataset and train a sentiment model. We have used the following torchtext example to train the model.

https://github.com/pytorch/text/tree/master/examples/text_classification

We have copied the files from above example and made small changes to save the model's state dict and added default values.

Training the model

Run the following commands to train the model :

./run_script.sh

The above command generated the model's state dict as model.pt and the vocab used during model training as source_vocab.pt

Serve the text classification model on TorchServe

  • Create a torch model archive using the torch-model-archiver utility to archive the above files.

    torch-model-archiver --model-name my_text_classifier --version 1.0 --model-file model.py --serialized-file model.pt --source-vocab source_vocab.pt --handler text_classifier --extra-files index_to_name.json

  • Register the model on TorchServe using the above model archive file and run digit recognition inference

    mkdir model_store
mv my_text_classifier.mar model_store/
torchserve --start --model-store model_store --models my_tc=my_text_classifier.mar
curl http://127.0.0.1:8080/predictions/my_tc -T examples/text_classification/sample_text.txt