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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a55bbdc90252c68f344648054524ce05b2115bacc93e0083186c909a940ab987
- Size of remote file:
- 295 MB
- SHA256:
- 23449b01d9c86e7ac89cfd0c6fe12b7b00ca09fa1de8c0f9ca6fff18197f4636
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