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: 844 Bytes
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tags:
- spacy
language:
- la
license: mit
---
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).
| Feature | Description |
| --- | --- |
| **Name** | `la_vectors_floret_lg` |
| **Version** | `3.8.0` |
| **spaCy** | `>=3.8.3,<3.9.0` |
| **Default Pipeline** | |
| **Components** | |
| **Vectors** | -1 keys, 200000 unique vectors (300 dimensions) |
| **Sources** | UD_Latin-Perseus<br>UD_Latin-PROIEL<br>UD_Latin-ITTB<br>UD_Latin-LLCT<br>UD_Latin-UDante<br>Wikipedia<br>OSCAR<br>Corpus Thomisticum<br>The Latin Library<br>CLTK-Tesserae Latin<br>Patrologia Latina |
| **License** | `MIT` |
| **Author** | [Patrick J. Burns](https://diyclassics.github.io/) | |