Instructions to use radlab/polish-fast-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radlab/polish-fast-tokenizer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radlab/polish-fast-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-4.0
language:
- pl
library_name: transformers
tags:
- tokenizer
- fast-tokenizer
- polish
datasets:
- radlab/legal-mc4-pl
- radlab/wikipedia-pl
- radlab/kgr10
- clarin-knext/msmarco-pl
- clarin-knext/fiqa-pl
- clarin-knext/scifact-pl
- clarin-knext/nfcorpus-pl
This is polish fast tokenizer.
Number of documents used to train tokenizer:
- 25 088 398
Sample usge with transformers:
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('radlab/polish-fast-tokenizer')
tokenizer.decode(tokenizer("Ala ma kota i psa").input_ids)