Translation
Transformers
PyTorch
TensorFlow
Safetensors
Hungarian
Ukrainian
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-base-hu-uk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-tc-base-hu-uk with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-base-hu-uk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-base-hu-uk") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-base-hu-uk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| hun-ukr flores101-dev 0.48918 19.8 997 21841 | |
| hun-ukr flores101-devtest 0.49490 19.8 1012 22810 | |
| hun-ukr tatoeba-test-v2020-07-28 0.61129 38.2 464 2568 | |
| hun-ukr tatoeba-test-v2021-03-30 0.60904 37.9 474 2623 | |
| hun-ukr tatoeba-test-v2021-08-07 0.61006 38.1 473 2606 | |