Instructions to use kravchenko/uk-mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kravchenko/uk-mt5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kravchenko/uk-mt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("kravchenko/uk-mt5-base") - Notebooks
- Google Colab
- Kaggle
The aim is to compress the mT5-base model to leave only the Ukrainian language and some basic English.
Reproduced the similar result (but with another language) from this medium article.
Results:
- 582M params -> 244M params (58%)
- 250K tokens -> 30K tokens
- 2.2GB size model -> 0.95GB size model
- Downloads last month
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