Instructions to use latincy/la_vectors_floret_lg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use latincy/la_vectors_floret_lg with spaCy:
!pip install https://huggingface.co/latincy/la_vectors_floret_lg/resolve/main/la_vectors_floret_lg-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("la_vectors_floret_lg") # Importing as module. import la_vectors_floret_lg nlp = la_vectors_floret_lg.load() - Notebooks
- Google Colab
- Kaggle
File size: 1,055 Bytes
bc4112a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | {
"lang":"la",
"name":"vectors_floret_lg",
"version":"3.8.0",
"description":"Code required to train lg floret embeddings for Latin on LatinCy Assets data. Based on spaCy project [Train floret vectors from Wikipedia and OSCAR](https://github.com/explosion/projects/tree/v3/pipelines/floret_wiki_oscar_vectors).",
"author":"Patrick J. Burns",
"email":"pjb311@nyu.edu",
"url":"https://diyclassics.github.io/",
"license":"MIT",
"spacy_version":">=3.8.3,<3.9.0",
"spacy_git_version":"be0fa81",
"vectors":{
"width":300,
"vectors":200000,
"keys":-1,
"name":"la_vectors_floret_lg.vectors"
},
"labels":{
},
"pipeline":[
],
"components":[
],
"disabled":[
],
"title":"la_vectors_floret_lg",
"sources":[
"UD_Latin-Perseus",
"UD_Latin-PROIEL",
"UD_Latin-ITTB",
"UD_Latin-LLCT",
"UD_Latin-UDante",
"Wikipedia",
"OSCAR",
"Corpus Thomisticum",
"The Latin Library",
"CLTK-Tesserae Latin",
"Patrologia Latina"
],
"requirements":[
"spacy>=3.8.3,<3.9.0"
]
} |