project.yml

title: "Dataset builder to HuggingFace Hub"
description: |
  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.

directories: ["assets", "corpus/spacy", "corpus/iob"]

vars:
  version: 1.0

assets:
  - dest: assets/corpus.tar.gz
    description: "Annotated TLUnified corpora in spaCy format with train, dev, and test splits."
    url: "https://storage.googleapis.com/ljvmiranda/calamanCy/tl_tlunified_gold/v${vars.version}/corpus.tar.gz"

commands:
  - name: "setup-data"
    help: "Prepare the Tagalog corpora used for training various spaCy components"
    script:
      - mkdir -p corpus/spacy
      - tar -xzvf assets/corpus.tar.gz -C corpus/spacy
      - python -m spacy_to_iob corpus/spacy/ corpus/iob/
    outputs:
      - corpus/iob/train.iob
      - corpus/iob/dev.iob
      - corpus/iob/test.iob

  - name: "upload-to-hf"
    help: "Upload dataset to HuggingFace Hub"
    script:
      - ls
    deps:
      - corpus/iob/train.iob
      - corpus/iob/dev.iob
      - corpus/iob/test.iob