Instructions to use Helsinki-NLP/opus-mt-sv-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-st 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-sv-st")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-st") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f30d308b3ecf5680355e4a9935352b5ee615c86c690ea78c0792d6e963981723
- Size of remote file:
- 301 MB
- SHA256:
- 5a0134b6978a215afc18c5fb60f6bf55077e281d3ff5055afb6d88cc9968fa70
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