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
| language: | |
| - uk | |
| - en | |
| - multilingual | |
| license: mit | |
| tags: | |
| - ukrainian | |
| - english | |
| This is a variant of the [google/mt5-base](https://huggingface.co/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 ](https://huggingface.co/cointegrated) | |
| ## Citing & Authors | |
| ``` | |
| @misc{Uaritm, | |
| title={SetFit: Classification of medical texts}, | |
| author={Vitaliy Ostashko}, | |
| year={2022}, | |
| url={https://esemi.org} | |
| } | |
| ``` | |