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
Add model description
Browse files
README.md
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| Feature | Description |
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| **Name** | `fa_floret` |
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| **Vectors** | -1 keys, 50000 unique vectors (300 dimensions) |
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| **Author** | [n/a]() |
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language:
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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.
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| Feature | Description |
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| **Name** | `fa_floret` |
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| **Vectors** | -1 keys, 50000 unique vectors (300 dimensions) |
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| **Sources** | n/a |
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| **License** | n/a |
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| **Author** | [n/a]() |
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