fa_floret_full_wiki

Persian floret static vector table: 50,000 rows x 300 dimensions, floret mode, minn=maxn=5, hash_count=2, trained with floret-torch on the full Persian Wikipedia dump. Vectors only, no pipeline components. Same table size as fa_floret_400k over a larger corpus; the fa_*_news_lg tier uses the 200,000-row fa_floret_wiki_200k instead.

Install

pip install https://huggingface.co/Phazel/fa_floret_full_wiki/resolve/main/fa_floret_full_wiki-0.1.0-py3-none-any.whl

Use

import spacy

nlp = spacy.load("fa_floret_full_wiki")
print(nlp.vocab.vectors.shape)
print(nlp("می‌رود")[0].has_vector)   # floret hashes subwords: always True

To train your own pipeline against it, unpack the wheel and point spaCy at the directory:

pip download --no-deps -d . https://huggingface.co/Phazel/fa_floret_full_wiki/resolve/main/fa_floret_full_wiki-0.1.0-py3-none-any.whl
python -m spacy train config.cfg --paths.vectors ./fa_floret_full_wiki

The table

Property Value
Rows 50,000
Dimensions 300
Mode floret
minn / maxn 5 / 5
hash_count 2
Corpus full Persian Wikipedia (fawiki) dump, extracted with WikiExtractor --no-templates, sentence-tokenized with spaCy blank("fa")
Trained with floret-torch (GPU port of explosion/floret), cbow, on a Colab T4

Other packages in this family

Pipeline Tier LAS ENTS_F Wheel
fa_dep_news_sm sm 85.15 - 7.9 MB
fa_core_news_sm sm 85.15 71.87 13.5 MB
fa_ent_news_sm sm - 71.87 5.9 MB
fa_dep_news_md md 86.34 - 62.6 MB
fa_core_news_md md 86.34 74.71 68.5 MB
fa_ent_news_md md - 74.71 60.6 MB
fa_dep_news_lg lg 86.60 - 229.3 MB
fa_core_news_lg lg 86.60 75.94 235.2 MB
fa_ent_news_lg lg - 75.94 227.3 MB
fa_core_news_trf trf 90.79 82.89 608.2 MB

Tiers: sm hash embeddings, no vectors, md 50k x 300d floret vectors, lg 200k x 300d floret vectors, trf fine-tuned transformer, GPU recommended.

Standalone vector tables, usable as --paths.vectors for your own training:

Vectors Rows Used by Wheel
fa_floret_400k 50,000 md tier 54.5 MB
fa_floret_full_wiki (this one) 50,000 no shipped pipeline 54.9 MB
fa_floret_wiki_200k 200,000 lg tier 221.3 MB

Training scripts, configs and evaluation: https://github.com/Fazel94/spacy-persian.

Sources

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