Instructions to use Helsinki-NLP/opus-mt-en-roa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-roa 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-en-roa")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-roa") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-roa", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3ab856f1dc51b7c18e26a256175e90598d3cb6bd5fce66e1a6c5ecb966df731
- Size of remote file:
- 295 MB
- SHA256:
- adca273d5dd130db09f1f8b031f0e98cab4019e3d71a491aa7b00dd1523422bf
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