tlunified-ner / README.md
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Implement simple workflow for parsing spaCy files
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🪐 spaCy Project: Dataset builder to HuggingFace Hub

This project contains utility scripts for uploading a dataset to HuggingFace Hub. We want to separate the spaCy dependencies from the loading script, so we're parsing the spaCy files independently.

The process goes like this: we download the raw corpus from Google Cloud Storage (GCS), convert the spaCy files into a readable IOB format, and parse that using our loading script (i.e., tlunified-ner.py).

We're also shipping the IOB file so that it's easier to access.

📋 project.yml

The project.yml defines the data assets required by the project, as well as the available commands and workflows. For details, see the spaCy projects documentation.

⏯ Commands

The following commands are defined by the project. They can be executed using spacy project run [name]. Commands are only re-run if their inputs have changed.

Command Description
setup-data Prepare the Tagalog corpora used for training various spaCy components
upload-to-hf Upload dataset to HuggingFace Hub

🗂 Assets

The following assets are defined by the project. They can be fetched by running spacy project assets in the project directory.

File Source Description
assets/corpus.tar.gz URL Annotated TLUnified corpora in spaCy format with train, dev, and test splits.