Instructions to use Phazel/fa_floret_400k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Phazel/fa_floret_400k with spaCy:
!pip install https://huggingface.co/Phazel/fa_floret_400k/resolve/main/fa_floret_400k-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("fa_floret_400k") # Importing as module. import fa_floret_400k nlp = fa_floret_400k.load() - Notebooks
- Google Colab
- Kaggle
File size: 1,008 Bytes
0f3b9a0 641ae6f 0f3b9a0 641ae6f 0f3b9a0 641ae6f | 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 | {
"lang": "fa",
"name": "floret_400k",
"version": "0.1.0",
"description": "Persian floret static vector table: 50,000 rows x 300 dimensions, floret mode, minn=maxn=5, hash_count=2, trained on 400,000 Persian documents. Vectors only, no pipeline components. This is the table used by the fa_*_news_md tier.",
"author": "Kiyarash Fazeli",
"email": "kiyarash@nlogn.ir",
"url": "https://github.com/Fazel94/spacy-persian",
"license": "CC BY-SA 4.0",
"sources": [
{
"name": "fa_floret static vectors (50k rows x 300d, floret mode, 400k Persian documents)",
"url": "https://github.com/Fazel94/spacy-persian",
"author": "Kiyarash Fazeli",
"license": "CC BY-SA 4.0"
}
],
"spacy_version": ">=3.8.15,<3.9.0",
"spacy_git_version": "f69c32f",
"vectors": {
"width": 300,
"vectors": 50000,
"keys": -1,
"name": "floret"
},
"labels": {},
"pipeline": [],
"components": [],
"disabled": [],
"requirements": [
"spacy>=3.8.15,<3.9.0"
]
}
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