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
v3.10.0: floret lg vectors retrained on v3.10 corpus; updated model card (model files + README)
347c1d9 verified | { | |
| "lang":"la", | |
| "name":"vectors_floret_lg", | |
| "version":"3.10.0", | |
| "description":"Floret word vectors for Latin, trained on 14.3M sentences (278M tokens) from 15 sources including UD/LASLA treebanks, CC100, Wikisource, Wikipedia, and other Latin corpora. Part of the LatinCy project.", | |
| "author":"Patrick J. Burns", | |
| "email":"patrick@diyclassics.org", | |
| "url":"https://huggingface.co/latincy", | |
| "license":"MIT", | |
| "spacy_version":">=3.8.11,<3.9.0", | |
| "spacy_git_version":"e7a662a", | |
| "vectors":{ | |
| "width":300, | |
| "vectors":200000, | |
| "keys":-1, | |
| "name":"la_vectors_floret_lg.vectors" | |
| }, | |
| "labels":{ | |
| }, | |
| "pipeline":[ | |
| ], | |
| "components":[ | |
| ], | |
| "disabled":[ | |
| ], | |
| "title":"la_vectors_floret", | |
| "sources":[ | |
| "UD_Latin-CIRCSE", | |
| "UD_Latin-Perseus", | |
| "UD_Latin-PROIEL", | |
| "UD_Latin-ITTB", | |
| "UD_Latin-LLCT", | |
| "UD_Latin-UDante", | |
| "CC100-Latin", | |
| "Latin Wikisource", | |
| "Latin Wikipedia", | |
| "The Latin Library", | |
| "CAMENA Neo-Latin", | |
| "Patrologia Latina", | |
| "Perseus Digital Library", | |
| "CLTK-Tesserae Latin", | |
| "CSEL", | |
| "digilibLT", | |
| "EDH", | |
| "Formulae", | |
| "Epistolae", | |
| "PTA" | |
| ], | |
| "requirements":[ | |
| "spacy>=3.8.11,<3.9.0" | |
| ] | |
| } |