Instructions to use Phazel/fa_floret_full_wiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Phazel/fa_floret_full_wiki with spaCy:
!pip install https://huggingface.co/Phazel/fa_floret_full_wiki/resolve/main/fa_floret_full_wiki-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("fa_floret_full_wiki") # Importing as module. import fa_floret_full_wiki nlp = fa_floret_full_wiki.load() - Notebooks
- Google Colab
- Kaggle
Floret vectors for Persian: fastText-style subwords hashed into a fixed 50,000-row Bloom table (300 dimensions), the same table shape as fa_floret_400k, retrained on the full Persian Wikipedia dump instead of a 400,000-document sample. Vectors-only package, no pipeline components — load with spacy.load or unpack and point --paths.vectors at it to train against.
| Feature | Description |
|---|---|
| Name | fa_floret |
| Version | 0.1.0 |
| spaCy | >=3.8.14,<3.9.0 |
| Default Pipeline | |
| Components | |
| Vectors | -1 keys, 50000 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
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