Translation
Transformers
PyTorch
TensorFlow
Safetensors
Turkish
Ukrainian
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-base-tr-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-tr-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-tr-uk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-base-tr-uk") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-base-tr-uk") - Notebooks
- Google Colab
- Kaggle
| tur-ukr flores101-devtest 0.49944 19.9 1012 22810 | |
| tur-ukr flores101-dev 0.49630 20.1 997 21841 | |
| tur-ukr tatoeba-test-v2020-07-28 0.63600 40.6 2500 12988 | |
| tur-ukr tatoeba-test-v2021-03-30 0.63616 40.6 4972 25856 | |
| tur-ukr tatoeba-test-v2021-08-07 0.63573 40.5 2520 13079 | |