Instructions to use Helsinki-NLP/opus-mt-ca-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-ca-de 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-ca-de")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ca-de") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ca-de") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48eaa2749402931171eff9278eb2af14482c919de1c6c7cc599a181175e1c368
- Size of remote file:
- 224 MB
- SHA256:
- 612da1979a8e3b16133c0c669a3fd05a9371b691cffc10460811a9c913cf5509
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