Translation
Transformers
PyTorch
TensorFlow
Safetensors
Romanian
Ukrainian
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-base-ro-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-ro-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-ro-uk")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-base-ro-uk") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-base-ro-uk") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 303ca94d395746cef1cbf6aabbe483c496cdc97332ee562743262ee70ae68203
- Size of remote file:
- 406 kB
- SHA256:
- a2958f09c12dddf95cebf171f7b1e802eea28ea36f7beb86464bf0bb571f1677
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