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
- Xet hash:
- 00dfe0e3905d5465a0cb546184e6abb22c0fc4dd34a6e0e86bf55dd29fe59c89
- Size of remote file:
- 835 kB
- SHA256:
- 2d1a616090c45d10a4b1dd1fe8f87a08348e3595af1f950d856a2e0178f79a1f
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