Publishing this model to the Hugging Face Hub

This directory is a complete Hugging Face model repository. It holds the loadable spaCy pipeline, the installable wheel, and the model card in README.md.

Path	What it is
`README.md`	model card, including the YAML front matter the Hub reads
`config.cfg`, `meta.json`	pipeline configuration and metadata
`tokenizer`, `vocab/`	tokeniser and vocabulary, including floret vectors
`tok2vec/`, `tagger/`, `morphologizer/`, `trainable_lemmatizer/`, `parser/`	trained component weights
`en_matilda_oe_ud-1.0.0-py3-none-any.whl`	installable package, for `pip install`
`.gitattributes`	LFS tracking for the binary weights

Loading the directory directly works without installing anything:

import spacy
nlp = spacy.load("model")

One-time setup

pip install huggingface_hub
huggingface-cli login

Creating the repository and uploading

Replace <org> with your Hugging Face user or organisation name.

huggingface-cli repo create en_matilda_oe_ud --type model

git lfs install
git clone https://huggingface.co/<org>/en_matilda_oe_ud hf-en_matilda_oe_ud
cp -R model/. hf-en_matilda_oe_ud/

cd hf-en_matilda_oe_ud
git add .
git commit -m "MATILDA Old English UD pipeline v1.0.0"
git push

.gitattributes already routes the weights and the wheel through Git LFS, so no further configuration is needed.

Checking the upload

Once the push completes, confirm that the published artefacts work end to end:

pip install https://huggingface.co/<org>/en_matilda_oe_ud/resolve/main/en_matilda_oe_ud-1.0.0-py3-none-any.whl
python -c "import spacy; print([(t.text, t.pos_, t.dep_) for t in spacy.load('en_matilda_oe_ud')('Hwæt we Gardena in geardagum þeodcyninga þrym gefrunon .')])"

On the Hub page, the metrics declared in the model-index block of the card should appear in the sidebar, and the language should show as ang.

Rebuilding the wheel

If the pipeline is retrained, regenerate the package before uploading:

python -m spacy package model/ dist/ --name matilda_oe_ud --version 1.0.0 --build wheel

The resulting wheel is written to dist/en_matilda_oe_ud-1.0.0/dist/.

Naming

The package is en_matilda_oe_ud while the repository language tag is ang. spaCy derives the package prefix from the pipeline's lang, which is en because no Old English tokeniser exists in spaCy and the baseline study used the English one. Every trained component is Old English only. The discrepancy is recorded in the model card so that users are not misled by the prefix.

Nerthus-Project
/

MATILDA_UD_parser_of_Old_English