Spert NLP Relation Extraction API deployed with torchserve for inference

Zichu Chen

Last update: Nov 24, 2021

Related tags

Text Data & NLP spert_torchserve

Overview

SpERT torchserve

Spert_torchserve is the Relation Extraction model (SpERT)Span-based Entity and Relation Transformer API deployed with pytorch/serve.

Install Requirements

pip install -r requirements.txt

Get your pretrained model

Train your own model with SpERT or use model trained by CoNLL04 from Huggingface. Only pytorch_model.bin is required to be archived. Download it here and save it into model directory.

You can also save your own model at Huggingface with large file storage.

Archive your model

Before serving model, pack the model and other configs into a .mar file.

torch-model-archiver --model-name spert --version 1.0 --model-file models.py --serialized-file model/pytorch_model.bin --export-path model_store --extra-files entities.py,input_reader.py,loss.py,prediction.py,sampling.py,conll04_types.json --handler spert_handler

This command pack all the needed files into a spert.mar file in model_store fold.

Serve the model

Start the service using the spert.mar with command:

torchserve --start --model-store model_store --models my_tc=spert.mar --ncs

Test

Post the text example "In 1822, the 18th president of the United States, Ulysses S. Grant, was born in Point Pleasant, Ohio" to:

http://127.0.0.1:8080/predictions/my_tc

A prediction would be returned:

{ "tokens": [ "In", "1822", ",", "the", "18th", "president", "of", "the", "United", "States", ",", "Ulysses", "S.", "Grant", ",", "was", "born", "in", "Point", "Pleasant", ",", "Ohio" ], "entities": [ { "type": "Loc", "start": 8, "end": 10 }, { "type": "Peop", "start": 11, "end": 14 }, { "type": "Loc", "start": 18, "end": 22 } ], "relations": [ { "type": "Live_In", "head": 1, "tail": 2 } ] }

References

Markus Eberts, Adrian Ulges. Span-based Joint Entity and Relation Extraction with Transformer Pre-training. 24th European Conference on Artificial Intelligence, 2020.

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Spert NLP Relation Extraction API deployed with torchserve for inference

Related tags

Overview

SpERT torchserve

Install Requirements

Get your pretrained model

Archive your model

Serve the model

Test

References

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