Instructions to use Helsinki-NLP/opus-mt-sv-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-sv-mt 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-mt")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-sv-mt") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-sv-mt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d30fe47475708de8c33b8644ae93a09098c6a78972e72d100d6a4e74e34807d
- Size of remote file:
- 296 MB
- SHA256:
- 77d546cf8161d613619a21865edde811948ce9461d37fe62cb9e605eccced015
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