Transformers
PyTorch
Ukrainian
English
multilingual
t5
text2text-generation
ukrainian
english
text-generation-inference
Instructions to use uaritm/ukrt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uaritm/ukrt5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uaritm/ukrt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("uaritm/ukrt5-base") - Notebooks
- Google Colab
- Kaggle
Quick Links
This is a variant of the google/mt5-base model, in which Ukrainian and 9% English words remain. This model has 252M parameters - 43% of the original size. Special thanks for the practical example and inspiration: cointegrated
Citing & Authors
@misc{Uaritm,
title={SetFit: Classification of medical texts},
author={Vitaliy Ostashko},
year={2022},
url={https://esemi.org}
}
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uaritm/ukrt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("uaritm/ukrt5-base")