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
Download meta.json from Phazel/fa_floret_400k: direct link, hf CLI and curl.
- Browser
- Download file 2.21 kB
-
https://huggingface.co/Phazel/fa_floret_400k/resolve/main/meta.json
- Command line
-
hf download hf://Phazel/fa_floret_400k/meta.json
-
curl -L -o meta.json https://huggingface.co/Phazel/fa_floret_400k/resolve/main/meta.json
2.21 kB
| { | |
| "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 with floret-torch on the first 400,000 articles of the Persian Wikipedia dump. 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, first 400,000 Persian Wikipedia articles, trained with floret-torch)", | |
| "url":"https://github.com/Fazel94/spacy-persian", | |
| "author":"Kiyarash Fazeli", | |
| "license":"CC BY-SA 4.0" | |
| }, | |
| { | |
| "name":"Persian Wikipedia dump (fawiki), the text the vector table is trained on", | |
| "url":"https://dumps.wikimedia.org/fawiki/", | |
| "author":"Wikipedia contributors", | |
| "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", | |
| "spacy>=3.8.15,<3.9.0" | |
| ], | |
| "vectors_training":{ | |
| "corpus":"first 400,000 articles of the Persian Wikipedia (`fawiki`) dump, extracted with WikiExtractor `--no-templates`, sentence-tokenized with spaCy `blank(\"fa\")`", | |
| "tokens":"~163M (project estimate for 400,000 articles; not measured for this run)", | |
| "epochs":5, | |
| "minn":5, | |
| "maxn":5, | |
| "hash_count":2, | |
| "min_count":20, | |
| "tool":"[floret-torch](https://github.com/Fazel94/floret-torch) (GPU port of [explosion/floret](https://github.com/explosion/floret)), cbow, on a Colab T4", | |
| "cli":"python -m floret_torch.train --input fa.txt --output fa \\\n --model cbow --mode floret --dim 300 --minn 5 --maxn 5 \\\n --neg 10 --epoch 5 --hashCount 2 --bucket 50000 \\\n --minCount 20 --lr 0.05 --batch 8192 --dtype fp32 --device cuda --seed 0", | |
| "dump_date":"not pinned: the run used `wikipedia_date: latest`" | |
| } | |
| } |