spacy-to-hf

A simple converter from Spacy Entities to Huggingface BILOU formatted data

I've always struggled to convert my spacy formatted spans into data that can be trained on using huggingface transformers. But Spacy's Entity format is the most intuitive format for tagging entities for NER.

This repo is a simple converter that leverages spacy.gold.biluo_tags_from_offsets and the SpaCy tokenizations repo that creates a 1-line function to convert spacy formatted spans to tokens and ner_tags that can be fed into any Token Classification Transformer

Installation

pip install spacy-to-hf
python -m spacy download en_core_web_sm

Usage

from spacy_to_hf import spacy_to_hf
from datasets import Dataset

span_data = [
    {
        "text": "I have a BSc (Bachelors of Computer Sciences) from NYU",
        "spans": [
            {"start": 9, "end": 12, "label": "degree"},
            {"start": 14, "end": 44, "label": "degree"},
            {"start": 51, "end": 54, "label": "university"}
        ]
    }
]
hf_data = spacy_to_hf(span_data, "bert-base-cased")
print(list(zip(hf_data["tokens"][0], hf_data["ner_tags"][0])))
ds = Dataset.from_dict(hf_data)

From here, you can label-index your ner_tags and prepare for fine-tuning

Project Setup

Project setup is credited to @anthonycorletti and his awesome repo https://github.com/anthonycorletti/python-project-template